Database system with database engine and separate distributed storage service

ABSTRACT

A database system may include a database service and a separate distributed storage service. The database service (or a database engine head node thereof) may be responsible for query parsing, optimization, and execution, transactionality, and consistency, while the storage service may be responsible for generating data pages from redo log records and for durability of those data pages. For example, in response to a write request directed to a particular data page, the database engine head node may generate a redo log record and send it, but not the data page, to a storage service node. The storage service node may store the redo log record and return a write acknowledgement to the database service prior to applying the redo log record. The server node may apply the redo log record and other redo log records to a previously stored version of the data page to create a current version.

RELATED APPLICATIONS

This application claims benefit of priority to U.S. ProvisionalApplication Ser. No. 61/794,572, entitled “DATABASE SYSTEM WITH DATABASEENGINE AND SEPARATE DISTRIBUTED STORAGE SERVICE”, which was filed Mar.15, 2013, and which is incorporated herein by reference in its entirety.

BACKGROUND

Distribution of various components of a software stack can in some casesprovide (or support) fault tolerance (e.g., through replication), higherdurability, and less expensive solutions (e.g., through the use of manysmaller, less-expensive components rather than fewer large, expensivecomponents). However, databases have historically been among thecomponents of the software stack that are least amenable todistribution. For example, it can be difficult to distribute databaseswhile still ensuring the so-called ACID properties (e.g., Atomicity,Consistency, Isolation, and Durability) that they are expected toprovide.

While most existing relational databases are not distributed, someexisting databases are “scaled out” (as opposed to being “scaled up” bymerely employing a larger monolithic system) using one of two commonmodels: a “shared nothing” model, and a “shared disk” model. In general,in a “shared nothing” model, received queries are decomposed intodatabase shards (each of which includes a component of the query), theseshards are sent to different compute nodes for query processing, and theresults are collected and aggregated before they are returned. Ingeneral, in a “shared disk” model, every compute node in a cluster hasaccess to the same underlying data. In systems that employ this model,great care must be taken to manage cache coherency. In both of thesemodels, a large, monolithic database is replicated on multiple nodes(including all of the functionality of a stand-alone database instance),and “glue” logic is added to stitch them together. For example, in the“shared nothing” model, the glue logic may provide the functionality ofa dispatcher that subdivides queries, sends them to multiple computenotes, and then combines the results. In a “shared disk” model, the gluelogic may serve to fuse together the caches of multiple nodes (e.g., tomanage coherency at the caching layer). These “shared nothing” and“shared disk” database systems can be costly to deploy and complex tomaintain, and may over-serve many database use cases.

In traditional database systems, the data managed by a database systemis stored on direct attached disks. If a disk fails, it is replaced andthen must be reloaded with the appropriate data. For example, in manysystems, crash recovery includes restoring the most recent snapshot froma backup HI system and then replaying any changes made since the lastsnapshot from that point forward. However, this approach does not scalewell to large databases.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating various components of a databasesoftware stack, according to one embodiment.

FIG. 2 is a block diagram illustrating a service system architecturethat may be configured to implement a web services-based databaseservice, according to some embodiments.

FIG. 3 is a block diagram illustrating various components of a databasesystem that includes a database engine and a separate distributeddatabase storage service, according to one embodiment.

FIG. 4 is a block diagram illustrating a distributed database-optimizedstorage system, according to one embodiment.

FIG. 5 is a flow diagram illustrating one embodiment of a method foraccessing data in a database system that includes a database engine anda separate distributed database storage service.

FIG. 6 is a block diagram illustrating the use of a separate distributeddatabase-optimized storage system in a database system, according to oneembodiment.

FIG. 7 is a flow diagram illustrating one embodiment of a method forperforming a write operation in a database system, from the perspectiveof the database engine.

FIG. 8 is a flow diagram illustrating one embodiment of a method forperforming a write operation in a database system, from the perspectiveof a distributed database-optimized storage system.

FIG. 9 is a block diagram illustrating how data and metadata may bestored on a given node of a distributed database-optimized storagesystem, according to one embodiment.

FIG. 10 is a block diagram illustrating an example configuration of adatabase volume, according to one embodiment.

FIG. 11 is a flow diagram illustrating one embodiment of a method forperforming a read operation in a database system, from the perspectiveof the database engine.

FIG. 12 is a flow diagram illustrating one embodiment of a method forperforming a read operation in a database system, from the perspectiveof a distributed database-optimized storage system.

FIG. 13 is a flow diagram illustrating one embodiment of a method forperforming read and write operations in a distributed database-optimizedstorage system that includes protection groups.

FIG. 14 is a block diagram illustrating a computer system configured toimplement at least a portion of a database system that includes adatabase engine and a separate distributed database storage service,according to various embodiments.

While embodiments are described herein by way of example for severalembodiments and illustrative drawings, those skilled in the art willrecognize that the embodiments are not limited to the embodiments ordrawings described. It should be understood, that the drawings anddetailed description thereto are not intended to limit embodiments tothe particular form disclosed, but on the contrary, the intention is tocover all modifications, equivalents and alternatives falling within thespirit and scope as defined by the appended claims. The headings usedherein are for organizational purposes only and are not meant to be usedto limit the scope of the description or the claims. As used throughoutthis application, the word “may” is used in a permissive sense (i.e.,meaning having the potential to), rather than the mandatory sense (i.e.,meaning must). Similarly, the words “include,” “including,” and“includes” mean including, but not limited to.

DETAILED DESCRIPTION

The systems described herein may, in some embodiments, implement a webservice that enables clients (e.g., subscribers) to operate a datastorage system in a cloud computing environment. In some embodiments,the data storage system may be an enterprise-class database system thatis highly scalable and extensible. In some embodiments, queries may bedirected to database storage that is distributed across multiplephysical resources, and the database system may be scaled up or down onan as needed basis. The database system may work effectively withdatabase schemas of various types and/or organizations, in differentembodiments. In some embodiments, clients/subscribers may submit queriesin a number of ways, e.g., interactively via an SQL interface to thedatabase system. In other embodiments, external applications andprograms may submit queries using Open Database Connectivity (ODBC)and/or Java Database Connectivity (JDBC) driver interfaces to thedatabase system.

More specifically, the systems described herein may, in someembodiments, implement a service-oriented database architecture in whichvarious functional components of a single database system areintrinsically distributed. For example, rather than lashing togethermultiple complete and monolithic database instances (each of which mayinclude extraneous functionality, such as an application server, searchfunctionality, or other functionality beyond that required to providethe core functions of a database), these systems may organize the basicoperations of a database (e.g., query processing, transactionmanagement, caching and storage) into tiers that may be individually andindependently scalable. For example, in some embodiments, each databaseinstance in the systems described herein may include a database tier(which may include a single database engine head node and a client-sidestorage system driver), and a separate, distributed storage system(which may include multiple storage nodes that collectively perform someof the operations traditionally performed in the database tier ofexisting systems).

As described in more detail herein, in some embodiments, some of thelowest level operations of a database, (e.g., backup, restore, snapshot,recovery, and/or various space management operations) may be offloadedfrom the database engine to the storage layer and distributed acrossmultiple nodes and storage devices. For example, in some embodiments,rather than the database engine applying changes to database tables (ordata pages thereof) and then sending the modified data pages to thestorage layer, the application of changes to the stored database tables(and data pages thereof) may be the responsibility of the storage layeritself. In such embodiments, redo log records, rather than modified datapages, may be sent to the storage layer, after which redo processing(e.g., the application of the redo log records) may be performedsomewhat lazily and in a distributed manner (e.g., by a backgroundprocess). In some embodiments, crash recovery (e.g., the rebuilding ofdata pages from stored redo log records) may also be performed by thestorage layer and may also be performed by a distributed (and, in somecases, lazy) background process.

In some embodiments, because only redo logs (and not modified datapages) are sent to the storage layer, there may be much less networktraffic between the database tier and the storage layer than in existingdatabase systems. In some embodiments, each redo log may be on the orderof one-tenth the size of the corresponding data page for which itspecifies a change. Note that requests sent from the database tier andthe distributed storage system may be asynchronous and that multiplesuch requests may be in flight at a time.

As previously noted, in typical large database systems, the entire dataset needs to be restored before the database system can be restartedfollowing a failure in the system. In these database systems, followinga crash, the system must determine the last point at which it was knownthat all of the data pages had been flushed to disk (e.g., a checkpoint)and must replay any change logs from that point forward. For example,before the database can be made available to handle incoming queriesfrom client processes, a system process must read in all of the datapages that were changed after the determined checkpoint and apply eachof the applicable change log records that had not already been appliedto those data pages.

In some embodiments, the database systems described herein may be ableto restart the database engine following a failure (e.g., to make thedatabase available to accept and service queries) almost immediatelyafter a database crash, without having to wait for the entire data setto be restored. Instead, queries can be received and serviced whilecrash recovery is performed lazily by one or more background threads.For example, following a crash, multiple background threads may operatein parallel on different storage nodes to reconstruct data pages fromcorresponding redo logs. In the meantime, if an incoming query targets adata page that has not yet been reconstructed, the storage layer may beconfigured to re-create that data page on the fly from the appropriateredo logs.

In general, after being given a piece of data, a primary requirement ofa database is that it can eventually give that piece of data back. To dothis, the database may include several different components (or tiers),each of which performs a different function. For example, a traditionaldatabase may be thought of as having three tiers: a first tier forperforming query parsing, optimization and execution; a second tier forproviding transactionality, recovery, and durability; and a third tierthat provides storage, either on locally attached disks or onnetwork-attached storage. As noted above, previous attempts to scale atraditional database have typically involved replicating all three tiersof the database and distributing those replicated database instancesacross multiple machines.

In some embodiments, the systems described herein may partitionfunctionality of a database system differently than in a traditionaldatabase, and may distribute only a subset of the functional components(rather than a complete database instance) across multiple machines inorder to implement scaling. For example, in some embodiments, aclient-facing tier may be configured to receive a request specifyingwhat data is to be stored or retrieved, but not how to store or retrievethe data. This tier may perform request parsing and/or optimization(e.g., SQL parsing and optimization), while another tier may beresponsible for query execution. In some embodiments, a third tier maybe responsible for providing transactionality and consistency ofresults. For example, this tier may be configured to enforce some of theso-called ACID properties, in particular, the Atomicity of transactionsthat target the database, maintaining Consistency within the database,and ensuring Isolation between the transactions that target thedatabase. In some embodiments, a fourth tier may then be responsible forproviding Durability of the stored data in the presence of various sortsof faults. For example, this tier may be responsible for change logging,recovery from a database crash, managing access to the underlyingstorage volumes and/or space management in the underlying storagevolumes.

FIG. 1 is a block diagram illustrating various components of a databasesoftware stack, according to one embodiment. As illustrated in thisexample, a database instance may include multiple functional components(or layers), each of which provides a portion of the functionality ofthe database instance. In this example, database instance 100 includes aquery parsing and query optimization layer (shown as 110), a queryexecution layer (shown as 120), a transactionality and consistencymanagement layer (shown as 130), and a durability and space managementlayer (shown as 140). As noted above, in some existing database systems,scaling a database instance may involve duplicating the entire databaseinstance one or more times (including all of the layers illustrated inFIG. 1), and then adding glue logic to stitch them together. In someembodiments, the systems described herein may instead offload thefunctionality of durability and space management layer 140 from thedatabase tier to a separate storage layer, and may distribute thatfunctionality across multiple storage nodes in the storage layer.

In some embodiments, the database systems described herein may retainmuch of the structure of the upper half of the database instanceillustrated in FIG. 1, but may redistribute responsibility for at leastportions of the backup, restore, snapshot, recovery, and/or variousspace management operations to the storage tier. Redistributingfunctionality in this manner and tightly coupling log processing betweenthe database tier and the storage tier may improve performance, increaseavailability and reduce costs, when compared to previous approaches toproviding a scalable database. For example, network and input/outputbandwidth requirements may be reduced, since only redo log records(which are much smaller in size than the actual data pages) may beshipped across nodes or persisted within the latency path of writeoperations. In addition, the generation of data pages can be doneindependently in the background on each storage node (as foregroundprocessing allows), without blocking incoming write operations. In someembodiments, the use of log-structured, non-overwrite storage may allowbackup, restore, snapshots, point-in-time recovery, and volume growthoperations to be performed more efficiently, e.g., by using onlymetadata manipulation rather than movement or copying of a data page. Insome embodiments, the storage layer may also assume the responsibilityfor the replication of data stored on behalf of clients (and/or metadataassociated with that data, such as redo log records) across multiplestorage nodes. For example, data (and/or metadata) may be replicatedlocally (e.g., within a single “availability zone” in which a collectionof storage nodes executes on its own physically distinct, independentinfrastructure) and/or across availability zones in a single region orin different regions.

In various embodiments, the database systems described herein maysupport a standard or custom application programming interface (API) fora variety of database operations. For example, the API may supportoperations for creating a database, creating a table, altering a table,creating a user, dropping a user, inserting one or more rows in a table,copying values, selecting data from within a table (e.g., querying atable), cancelling or aborting a query, and/or other operations.

In some embodiments, the database tier of a database instance mayinclude a database engine head node server that receives read and/orwrite requests from various client programs (e.g., applications) and/orsubscribers (users), then parses them and develops an execution plan tocarry out the associated database operation(s). For example, thedatabase engine head node may develop the series of steps necessary toobtain results for complex queries and joins. In some embodiments, thedatabase engine head node may manage communications between the databasetier of the database system and clients/subscribers, as well ascommunications between the database tier and a separate distributeddatabase-optimized storage system.

In some embodiments, the database engine head node may be responsiblefor receiving SQL requests from end clients through a JDBC or ODBCinterface and for performing SQL processing and transaction management(which may include locking) locally. However, rather than generatingdata pages locally, the database engine head node (or various componentsthereof) may generate redo log records and may ship them to theappropriate nodes of a separate distributed storage system. In someembodiments, a client-side driver for the distributed storage system maybe hosted on the database engine head node and may be responsible forrouting redo log records to the storage system node (or nodes) thatstore the segments (or data pages thereof) to which those redo logrecords are directed. For example, in some embodiments, each segment maybe mirrored (or otherwise made durable) on multiple storage system nodesthat form a protection group. In such embodiments, the client-sidedriver may keep track of the nodes on which each segment is stored andmay route redo logs to all of the nodes on which a segment is stored(e.g., asynchronously and in parallel, at substantially the same time),when a client request is received. As soon as the client-side driverreceives an acknowledgement back from a write quorum of the storagenodes in the protection group (which may indicate that the redo logrecord has been written to the storage node), it may send anacknowledgement of the requested change to the database tier (e.g., tothe database engine head node). For example, in embodiments in whichdata is made durable through the use of protection groups, the databaseengine head node may not be able to commit a transaction until andunless the client-side driver receives a reply from enough storage nodeinstances to constitute a write quorum.

Similarly, for a read request directed to a particular segment, theclient-side driver may route the read request to all of the nodes onwhich the segment is stored (e.g., asynchronously and in parallel, atsubstantially the same time). As soon as the client-side driver receivesthe requested data from a read quorum of the storage nodes in theprotection group, it may return the requested data to the database tier(e.g., to the database engine head node).

In some embodiments, the database tier (or more specifically, thedatabase engine head node) may include a cache in which recentlyaccessed data pages are held temporarily. In such embodiments, if awrite request is received that targets a data page held in such a cache,in addition to shipping a corresponding redo log record to the storagelayer, the database engine may apply the change to the copy of the datapage held in its cache. However, unlike in other database systems, adata page held in this cache may not ever be flushed to the storagelayer, and it may be discarded at any time (e.g., at any time after theredo log record for a write request that was most recently applied tothe cached copy has been sent to the storage layer and acknowledged).The cache may implement any of various locking mechanisms to controlaccess to the cache by at most one writer (or multiple readers) at atime, in different embodiments. Note, however, that in embodiments thatinclude such a cache, the cache may not be distributed across multiplenodes, but may exist only on the database engine head node for a givendatabase instance. Therefore, there may be no cache coherency orconsistency issues to manage.

In some embodiments, the database tier may support the use ofsynchronous or asynchronous read replicas in the system, e.g., read-onlycopies of data on different nodes of the database tier to which readrequests can be routed. In such embodiments, if the database engine headnode for a given database table receives a read request directed to aparticular data page, it may route the request to any one (or aparticular one) of these read-only copies. In some embodiments, theclient-side driver in the database engine head node may be configured tonotify these other nodes about updates and/or invalidations to cacheddata pages (e.g., in order to prompt them to invalidate their caches,after which they may request updated copies of updated data pages fromthe storage layer).

In some embodiments, the client-side driver running on the databaseengine head node may expose a private interface to the storage tier. Insome embodiments, it may also expose a traditional iSCSI interface toone or more other components (e.g., other database engines or virtualcomputing services components). In some embodiments, storage for adatabase instance in the storage tier may be modeled as a single volumethat can grow in size without limits, and that can have an unlimitednumber of IOPS associated with it. When a volume is created, it may becreated with a specific size, with a specific availability/durabilitycharacteristic (e.g., specifying how it is replicated), and/or with anIOPS rate associated with it (e.g., both peak and sustained). Forexample, in some embodiments, a variety of different durability modelsmay be supported, and users/subscribers may be able to specify, fortheir database tables, a number of replication copies, zones, or regionsand/or whether replication is synchronous or asynchronous based upontheir durability, performance and cost objectives.

In some embodiments, the client side driver may maintain metadata aboutthe volume and may directly send asynchronous requests to each of thestorage nodes necessary to fulfill read requests and write requestswithout requiring additional hops between storage nodes. For example, insome embodiments, in response to a request to make a change to adatabase table, the client-side driver may be configured to determinethe one or more nodes that are implementing the storage for the targeteddata page, and to route the redo log record(s) specifying that change tothose storage nodes. The storage nodes may then be responsible forapplying the change specified in the redo log record to the targeteddata page at some point in the future. As writes are acknowledged backto the client-side driver, the client-side driver may advance the pointat which the volume is durable and may acknowledge commits back to thedatabase tier. As previously noted, in some embodiments, the client-sidedriver may not ever send data pages to the storage node servers. Thismay not only reduce network traffic, but may also remove the need forthe checkpoint or background writer threads that constrainforeground-processing throughput in previous database systems.

In some embodiments, many read requests may be served by the databaseengine head node cache. However, write requests may require durability,since large-scale failure events may be too common to allow onlyin-memory replication. Therefore, the systems described herein may beconfigured to minimize the cost of the redo log record write operationsthat are in the foreground latency path by implementing data storage inthe storage tier as two regions: a small append-only log-structuredregion into which redo log records are written when they are receivedfrom the database tier, and a larger region in which log records arecoalesced together to create new versions of data pages in thebackground. In some embodiments, an in-memory structure may bemaintained for each data page that points to the last redo log recordfor that page, backward chaining log records until an instantiated datablock is referenced. This approach may provide good performance formixed read-write workloads, including in applications in which reads arelargely cached.

In some embodiments, because accesses to the log-structured data storagefor the redo log records may consist of a series of sequentialinput/output operations (rather than random input/output operations),the changes being made may be tightly packed together. It should also benoted that, in contrast to existing systems in which each change to adata page results in two input/output operations to persistent datastorage (one for the redo log and one for the modified data pageitself), in some embodiments, the systems described herein may avoidthis “write amplification” by coalescing data pages at the storage nodesof the distributed storage system based on receipt of the redo logrecords.

As previously noted, in some embodiments, the storage tier of thedatabase system may be responsible for taking database snapshots.However, because the storage tier implements log-structured storage,taking a snapshot of a data page (e.g., a data block) may includerecording a timestamp associated with the redo log record that was mostrecently applied to the data page/block (or a timestamp associated withthe most recent operation to coalesce multiple redo log records tocreate a new version of the data page/block), and preventing garbagecollection of the previous version of the page/block and any subsequentlog entries up to the recorded point in time. For example, taking adatabase snapshot may not require reading, copying, or writing the datablock, as would be required when employing an off-volume backupstrategy. In some embodiments, the space requirements for snapshots maybe minimal, since only modified data would require additional space,although user/subscribers may be able to choose how much additionalspace they want to keep for on-volume snapshots in addition to theactive data set. In different embodiments, snapshots may be discrete(e.g., each snapshot may provide access to all of the data in a datapage as of a specific point in time) or continuous (e.g., each snapshotmay provide access to all versions of the data that existing in a datapage between two points in time). In some embodiments, reverting to aprior snapshot may include recording a log record to indicate that allredo log records and data pages since that snapshot are invalid andgarbage collectable, and discarding all database cache entries after thesnapshot point. In such embodiments, no roll-forward may be requiredsince the storage system will, on a block-by-block basis, apply redo logrecords to data blocks as requested and in the background across allnodes, just as it does in normal forward read/write processing. Crashrecovery may thereby be made parallel and distributed across nodes.

One embodiment of a service system architecture that may be configuredto implement a web services-based database service is illustrated inFIG. 2. In the illustrated embodiment, a number of clients (shown asdatabase clients 250 a-250 n) may be configured to interact with a webservices platform 200 via a network 260. Web services platform 200 maybe configured to interface with one or more instances of a databaseservice 210, a distributed database-optimized storage service 220 and/orone or more other virtual computing services 230. It is noted that whereone or more instances of a given component may exist, reference to thatcomponent herein may be made in either the singular or the plural.However, usage of either form is not intended to preclude the other.

In various embodiments, the components illustrated in FIG. 2 may beimplemented directly within computer hardware, as instructions directlyor indirectly executable by computer hardware (e.g., a microprocessor orcomputer system), or using a combination of these techniques. Forexample, the components of FIG. 2 may be implemented by a system thatincludes a number of computing nodes (or simply, nodes), each of whichmay be similar to the computer system embodiment illustrated in FIG. 14and described below. In various embodiments, the functionality of agiven service system component (e.g., a component of the databaseservice or a component of the storage service) may be implemented by aparticular node or may be distributed across several nodes. In someembodiments, a given node may implement the functionality of more thanone service system component (e.g., more than one database servicesystem component).

Generally speaking, clients 250 may encompass any type of clientconfigurable to submit web services requests to web services platform200 via network 260, including requests for database services. Forexample, a given client 250 may include a suitable version of a webbrowser, or may include a plug-in module or other type of code moduleconfigured to execute as an extension to or within an executionenvironment provided by a web browser. Alternatively, a client 250(e.g., a database service client) may encompass an application such as adatabase application (or user interface thereof), a media application,an office application or any other application that may make use ofpersistent storage resources to store and/or access one or more databasetables. In some embodiments, such an application may include sufficientprotocol support (e.g., for a suitable version of Hypertext TransferProtocol (HTTP)) for generating and processing web services requestswithout necessarily implementing full browser support for all types ofweb-based data. That is, client 250 may be an application configured tointeract directly with web services platform 200. In some embodiments,client 250 may be configured to generate web services requests accordingto a Representational State Transfer (REST)-style web servicesarchitecture, a document- or message-based web services architecture, oranother suitable web services architecture.

In some embodiments, a client 250 (e.g., a database service client) maybe configured to provide access to web services-based storage ofdatabase tables to other applications in a manner that is transparent tothose applications. For example, client 250 may be configured tointegrate with an operating system or file system to provide storage inaccordance with a suitable variant of the storage models describedherein. However, the operating system or file system may present adifferent storage interface to applications, such as a conventional filesystem hierarchy of files, directories and/or folders. In such anembodiment, applications may not need to be modified to make use of thestorage system service model of FIG. 1. Instead, the details ofinterfacing to Web services platform 200 may be coordinated by client250 and the operating system or file system on behalf of applicationsexecuting within the operating system environment.

Clients 250 may convey web services requests to and receive responsesfrom web services platform 200 via network 260. In various embodiments,network 260 may encompass any suitable combination of networkinghardware and protocols necessary to establish web-based communicationsbetween clients 250 and platform 200. For example, network 260 maygenerally encompass the various telecommunications networks and serviceproviders that collectively implement the Internet. Network 260 may alsoinclude private networks such as local area networks (LANs) or wide areanetworks (WANs) as well as public or private wireless networks. Forexample, both a given client 250 and web services platform 200 may berespectively provisioned within enterprises having their own internalnetworks. In such an embodiment, network 260 may include the hardware(e.g., modems, routers, switches, load balancers, proxy servers, etc.)and software (e.g., protocol stacks, accounting software,firewall/security software, etc.) necessary to establish a networkinglink between given client 250 and the Internet as well as between theInternet and web services platform 200. It is noted that in someembodiments, clients 250 may communicate with web services platform 200using a private network rather than the public Internet. For example,clients 250 may be provisioned within the same enterprise as a databaseservice system (e.g., a system that implements database service 210and/or distributed database-optimized storage service 220). In such acase, clients 250 may communicate with platform 200 entirely through aprivate network 260 (e.g., a LAN or WAN that may use Internet-basedcommunication protocols but which is not publicly accessible).

Generally speaking, web services platform 200 may be configured toimplement one or more service endpoints configured to receive andprocess web services requests, such as requests to access data pages (orrecords thereof). For example, web services platform 200 may includehardware and/or software configured to implement a particular endpoint,such that an HTTP-based web services request directed to that endpointis properly received and processed. In one embodiment, web servicesplatform 200 may be implemented as a server system configured to receiveweb services requests from clients 250 and to forward them to componentsof a system that implements database service 210, distributeddatabase-optimized storage service 220 and/or another virtual computingservice 230 for processing. In other embodiments, web services platform200 may be configured as a number of distinct systems (e.g., in acluster topology) implementing load balancing and other requestmanagement features configured to dynamically manage large-scale webservices request processing loads. In various embodiments, web servicesplatform 200 may be configured to support REST-style or document-based(e.g., SOAP-based) types of web services requests.

In addition to functioning as an addressable endpoint for clients' webservices requests, in some embodiments, web services platform 200 mayimplement various client management features. For example, platform 200may coordinate the metering and accounting of client usage of webservices, including storage resources, such as by tracking theidentities of requesting clients 250, the number and/or frequency ofclient requests, the size of data tables (or records thereof) stored orretrieved on behalf of clients 250, overall storage bandwidth used byclients 250, class of storage requested by clients 250, or any othermeasurable client usage parameter. Platform 200 may also implementfinancial accounting and billing systems, or may maintain a database ofusage data that may be queried and processed by external systems forreporting and billing of client usage activity. In certain embodiments,platform 200 may be configured to collect, monitor and/or aggregate avariety of storage service system operational metrics, such as metricsreflecting the rates and types of requests received from clients 250,bandwidth utilized by such requests, system processing latency for suchrequests, system component utilization (e.g., network bandwidth and/orstorage utilization within the storage service system), rates and typesof errors resulting from requests, characteristics of stored andrequested data pages or records thereof (e.g., size, data type, etc.),or any other suitable metrics. In some embodiments such metrics may beused by system administrators to tune and maintain system components,while in other embodiments such metrics (or relevant portions of suchmetrics) may be exposed to clients 250 to enable such clients to monitortheir usage of database service 210, distributed database-optimizedstorage service 220 and/or another virtual computing service 230 (or theunderlying systems that implement those services).

In some embodiments, platform 200 may also implement user authenticationand access control procedures. For example, for a given web servicesrequest to access a particular database table, platform 200 may beconfigured to ascertain whether the client 250 associated with therequest is authorized to access the particular database table. Platform200 may determine such authorization by, for example, evaluating anidentity, password or other credential against credentials associatedwith the particular database table, or evaluating the requested accessto the particular database table against an access control list for theparticular database table. For example, if a client 250 does not havesufficient credentials to access the particular database table, platform200 may reject the corresponding web services request, for example byreturning a response to the requesting client 250 indicating an errorcondition. Various access control policies may be stored as records orlists of access control information by database service 210, distributeddatabase-optimized storage service 220 and/or other virtual computingservices 230.

It is noted that while web services platform 200 may represent theprimary interface through which clients 250 may access the features of adatabase system that implements database service 210, it need notrepresent the sole interface to such features. For example, an alternateAPI that may be distinct from a web services interface may be used toallow clients internal to the enterprise providing the database systemto bypass web services platform 200. Note that in many of the examplesdescribed herein, distributed database-optimized storage service 220 maybe internal to a computing system or an enterprise system that providesdatabase services to clients 250, and may not be exposed to externalclients (e.g., users or client applications). In such embodiments, theinternal “client” (e.g., database service 210) may access distributeddatabase-optimized storage service 220 over a local or private network,shown as the solid line between distributed database-optimized storageservice 220 and database service 210 (e.g., through an API directlybetween the systems that implement these services). In such embodiments,the use of distributed database-optimized storage service 220 in storingdatabase tables on behalf of clients 250 may be transparent to thoseclients. In other embodiments, distributed database-optimized storageservice 220 may be exposed to clients 250 through web services platform200 to provide storage of database tables or other information forapplications other than those that rely on database service 210 fordatabase management. This is illustrated in FIG. 2 by the dashed linebetween web services platform 200 and distributed database-optimizedstorage service 220. In such embodiments, clients of the distributeddatabase-optimized storage service 220 may access distributeddatabase-optimized storage service 220 via network 260 (e.g., over theInternet). In some embodiments, a virtual computing service 230 may beconfigured to receive storage services from distributeddatabase-optimized storage service 220 (e.g., through an API directlybetween the virtual computing service 230 and distributeddatabase-optimized storage service 220) to store objects used inperforming computing services 230 on behalf of a client 250. This isillustrated in FIG. 2 by the dashed line between virtual computingservice 230 and distributed database-optimized storage service 220. Insome cases, the accounting and/or credentialing services of platform 200may be unnecessary for internal clients such as administrative clientsor between service components within the same enterprise.

Note that in various embodiments, different storage policies may beimplemented by database service 210 and/or distributeddatabase-optimized storage service 220. Examples of such storagepolicies may include a durability policy (e.g., a policy indicating thenumber of instances of a database table (or data page thereof) that willbe stored and the number of different nodes on which they will bestored) and/or a load balancing policy (which may distribute databasetables, or data pages thereof, across different nodes, volumes and/ordisks in an attempt to equalize request traffic). In addition, differentstorage policies may be applied to different types of stored items byvarious one of the services. For example, in some embodiments,distributed database-optimized storage service 220 may implement ahigher durability for redo log records than for data pages.

FIG. 3 is a block diagram illustrating various components of a databasesystem that includes a database engine and a separate distributeddatabase storage service, according to one embodiment. In this example,database system 300 includes a respective database engine head node 320for each of several database tables and a distributed database-optimizedstorage service 310 (which may or may not be visible to the clients ofthe database system, shown as database clients 350 a-350 n). Asillustrated in this example, one or more of database clients 350 a-350 nmay access a database head node 320 (e.g., head node 320 a, head node320 b, or head node 320 c, each of which is a component of a respectivedatabase instance) via network 360 (e.g., these components may benetwork-addressable and accessible to the database clients 350 a-350 n).However, distributed database-optimized storage service 310, which maybe employed by the database system to store data pages of one or moredatabase tables (and redo log records and/or other metadata associatedtherewith) on behalf of database clients 350 a-350 n, and to performother functions of the database system as described herein, may or maynot be network-addressable and accessible to the storage clients 350a-350 n, in different embodiments. For example, in some embodiments,distributed database-optimized storage service 310 may perform variousstorage, access, change logging, recovery, and/or space managementoperations in a manner that is invisible to storage clients 350 a-350 n.

As previously noted, each database instance may include a singledatabase engine head node 320 that receives requests from various clientprograms (e.g., applications) and/or subscribers (users), then parsesthem, optimizes them, and develops an execution plan to carry out theassociated database operation(s). In the example illustrated in FIG. 3,a query parsing, optimization, and execution component 305 of databaseengine head node 320 a may perform these functions for queries that arereceived from database client 350 a and that target the databaseinstance of which database engine head node 320 a is a component. Insome embodiments, query parsing, optimization, and execution component305 may return query responses to database client 350 a, which mayinclude write acknowledgements, requested data pages (or portionsthereof), error messages, and or other responses, as appropriate. Asillustrated in this example, database engine head node 320 a may alsoinclude a client-side storage service driver 325, which may route readrequests and/or redo log records to various storage nodes withindistributed database-optimized storage service 310, receive writeacknowledgements from distributed database-optimized storage service310, receive requested data pages from distributed database-optimizedstorage service 310, and/or return data pages, error messages, or otherresponses to query parsing, optimization, and execution component 305(which may, in turn, return them to database client 350 a).

In this example, database engine head node 320 a includes a data pagecache 335, in which data pages that were recently accessed may betemporarily held. As illustrated in FIG. 3, database engine head node320 a may also include a transaction and consistency managementcomponent 330, which may be responsible for providing transactionalityand consistency in the database instance of which database engine headnode 320 a is a component. For example, this component may beresponsible for ensuring the Atomicity, Consistency, and Isolationproperties of the database instance and the transactions that aredirected that the database instance. As illustrated in FIG. 3, databaseengine head node 320 a may also include a transaction log 340 and anundo log 345, which may be employed by transaction and consistencymanagement component 330 to track the status of various transactions androll back any locally cached results of transactions that do not commit.

Note that each of the other database engine head nodes 320 illustratedin FIG. 3 (e.g., 320 b and 320 c) may include similar components and mayperform similar functions for queries received by one or more ofdatabase clients 350 a-350 n and directed to the respective databaseinstances of which it is a component.

In some embodiments, the distributed database-optimized storage systemsdescribed herein may organize data in various logical volumes, segments,and pages for storage on one or more storage nodes. For example, in someembodiments, each database table is represented by a logical volume, andeach logical volume is segmented over a collection of storage nodes.Each segment, which lives on a particular one of the storage nodes,contains a set of contiguous block addresses. In some embodiments, eachdata page is stored in a segment, such that each segment stores acollection of one or more data pages and a change log(also referred toas a redo log) for each data page that it stores. As described in detailherein, the storage nodes may be configured to receive redo log records(which may also be referred to herein as ULRs) and to coalesce them tocreate new versions of the corresponding data pages and/or additional orreplacement log records (e.g., lazily and/or in response to a requestfor a data page or a database crash). In some embodiments, data pagesand/or change logs may be mirrored across multiple storage nodes,according to a variable configuration (which may be specified by theclient on whose behalf the database table is being maintained in thedatabase system). For example, in different embodiments, one, two, orthree copies of the data or change logs may be stored in each of one,two, or three different availability zones or regions, according to adefault configuration, an application-specific durability preference, ora client-specified durability preference.

As used herein, the following terms may be used to describe theorganization of data by a distributed database-optimized storage system,according to various embodiments.

Volume: A volume is a logical concept representing a highly durable unitof storage that a user/client/application of the storage systemunderstands. More specifically, a volume is a distributed store thatappears to the user/client/application as a single consistent orderedlog of write operations to various user pages of a database table. Eachwrite operation may be encoded in a User Log Record (ULR), whichrepresents a logical, ordered mutation to the contents of a single userpage within the volume. As noted above, a ULR may also be referred toherein as a redo log record. Each ULR may include a unique LSN, orLogical Sequence Number. Each ULR may be persisted to one or moresynchronous segments in the distributed store that form a ProtectionGroup (PG), to provide high durability and availability for the ULR. Avolume may provide an LSN-type read/write interface for a variable-sizecontiguous range of bytes.

In some embodiments, a volume may consist of multiple extents, each madedurable through a protection group. In such embodiments, a volume mayrepresent a unit of storage composed of a mutable contiguous sequence ofVolume Extents. Reads and writes that are directed to a volume may bemapped into corresponding reads and writes to the constituent volumeextents. In some embodiments, the size of a volume may be changed byadding or removing volume extents from the end of the volume.

Segment: A segment is a limited-durability unit of storage assigned to asingle storage node. More specifically, a segment provides limitedbest-effort durability (e.g., a persistent, but non-redundant singlepoint of failure that is a storage node) for a specific fixed-size byterange of data. This data may in some cases be a mirror ofuser-addressable data, or it may be other data, such as volume metadataor erasure coded bits, in various embodiments. A given segment may liveon exactly one storage node. Within a storage node, multiple segmentsmay live on each SSD, and each segment may be restricted to one SSD(e.g., a segment may not span across multiple SSDs). In someembodiments, a segment may not be required to occupy a contiguous regionon an SSD; rather there may be an allocation map in each SSD describingthe areas that are owned by each of the segments. As noted above, aprotection group may consist of multiple segments spread across multiplestorage nodes. In some embodiments, a segment may provide an LSN-typeread/write interface for a fixed-size contiguous range of bytes (wherethe size is defined at creation). In some embodiments, each segment maybe identified by a Segment UUID (e.g., a universally unique identifierof the segment).

Storage page: A storage page is a block of memory, generally of fixedsize. In some embodiments, each page is a block of memory (e.g., ofvirtual memory, disk, or other physical memory) of a size defined by theoperating system, and may also be referred to herein by the term “datablock”. More specifically, a storage page may be a set of contiguoussectors. It may serve as the unit of allocation in SSDs, as well as theunit in log pages for which there is a header and metadata. In someembodiments, and in the context of the database systems describedherein, the term “page” or “storage page” may refer to a similar blockof a size defined by the database configuration, which may typically amultiple of 2, such as 4096, 8192, 16384, or 32768 bytes.

Log page: A log page is a type of storage page that is used to store logrecords (e.g., redo log records or undo log records). In someembodiments, log pages may be identical in size to storage pages. Eachlog page may include a header containing metadata about that log page,e.g., metadata identifying the segment to which it belongs. Note that alog page is a unit of organization and may not necessarily be the unitof data included in write operations. For example, in some embodiments,during normal forward processing, write operations may write to the tailof the log one sector at a time.

Log Records: Log records (e.g., the individual elements of a log page)may be of several different classes. For example, User Log Records(ULRs), which are created and understood by users/clients/applicationsof the storage system, may be used to indicate changes to user data in avolume. Control Log Records (CLRs), which are generated by the storagesystem, may contain control information used to keep track of metadatasuch as the current unconditional volume durable LSN (VDL). Null LogRecords (NLRB) may in some embodiments be used as padding to fill inunused space in a log sector or log page. In some embodiments, there maybe various types of log records within each of these classes, and thetype of a log record may correspond to a function that needs to beinvoked to interpret the log record. For example, one type may representall the data of a user page in compressed format using a specificcompression format; a second type may represent new values for a byterange within a user page; a third type may represent an incrementoperation to a sequence of bytes interpreted as an integer; and a fourthtype may represent copying one byte range to another location within thepage. In some embodiments, log record types may be identified by GUIDs(rather than by integers or enums), which may simplify versioning anddevelopment, especially for ULRs.

Payload: The payload of a log record is the data or parameter valuesthat are specific to the log record or to log records of a particulartype. For example, in some embodiments, there may be a set of parametersor attributes that most (or all) log records include, and that thestorage system itself understands. These attributes may be part of acommon log record header/structure, which may be relatively smallcompared to the sector size. In addition, most log records may includeadditional parameters or data specific to that log record type, and thisadditional information may be considered the payload of that log record.In some embodiments, if the payload for a particular ULR is larger thanthe user page size, it may be replaced by an absolute ULR (an AULR)whose payload includes all the data for the user page. This may enablethe storage system to enforce an upper limit on the size of the payloadfor ULRs that is equal to the size of user pages.

Note that when storing log records in the segment log, the payload maybe stored along with the log header, in some embodiments. In otherembodiments, the payload may be stored in a separate location, andpointers to the location at which that payload is stored may be storedwith the log header. In still other embodiments, a portion of thepayload may be stored in the header, and the remainder of the payloadmay be stored in a separate location. If the entire payload is storedwith the log header, this may be referred to as in-band storage;otherwise the storage may be referred to as being out-of-band. In someembodiments, the payloads of most large AULRs may be stored out-of-bandin the cold zone of log(which is described below).

User pages: User pages are the byte ranges (of a fixed size) andalignments thereof for a particular volume that are visible tousers/clients of the storage system. User pages are a logical concept,and the bytes in particular user pages may or not be stored in anystorage page as-is. The size of the user pages for a particular volumemay be independent of the storage page size for that volume. In someembodiments, the user page size may be configurable per volume, anddifferent segments on a storage node may have different user page sizes.In some embodiments, user page sizes may be constrained to be a multipleof the sector size (e.g., 4 KB), and may have an upper limit (e.g., 64KB). The storage page size, on the other hand, may be fixed for anentire storage node and may not change unless there is a change to theunderlying hardware.

Data page: A data page is a type of storage page that is used to storeuser page data in compressed form. In some embodiments every piece ofdata stored in a data page is associated with a log record, and each logrecord may include a pointer to a sector within a data page (alsoreferred to as a data sector). In some embodiments, data pages may notinclude any embedded metadata other than that provided by each sector.There may be no relationship between the sectors in a data page.Instead, the organization into pages may exist only as an expression ofthe granularity of the allocation of data to a segment.

Storage node: A storage node is a single virtual machine that on whichstorage node server code is deployed. Each storage node may containmultiple locally attached SSDs, and may provide a network API for accessto one or more segments. In some embodiments, various nodes may be on anactive list or on a degraded list (e.g., if they are slow to respond orare otherwise impaired, but are not completely unusable). In someembodiments, the client-side driver may assist in (or be responsiblefor) classifying nodes as active or degraded, for determining if andwhen they should be replaced, and/or for determining when and how toredistribute data among various nodes, based on observed performance.

SSD: As referred to herein, the term “SSD” may refer to a local blockstorage volume as seen by the storage node, regardless of the type ofstorage employed by that storage volume, e.g., disk, a solid-statedrive, a battery-backed RAM, an NVMRAM device (e.g., one or moreNVDIMMs), or another type of persistent storage device. An SSD is notnecessarily mapped directly to hardware. For example, a singlesolid-state storage device might be broken up into multiple localvolumes where each volume is split into and striped across multiplesegments, and/or a single drive may be broken up into multiple volumessimply for ease of management, in different embodiments. In someembodiments, each SSD may store an allocation map at a single fixedlocation. This map may indicate which storage pages that are owned byparticular segments, and which of these pages are log pages (as opposedto data pages). In some embodiments, storage pages may be pre-allocatedto each segment so that forward processing may not need to wait forallocation. Any changes to the allocation map may need to be madedurable before newly allocated storage pages are used by the segments.

One embodiment of a distributed database-optimized storage system isillustrated by the block diagram in FIG. 4. In this example, a databasesystem 400 includes a distributed database-optimized storage system 410,which communicates with a database engine head node 420 overinterconnect 460. As in the example illustrated in FIG. 3, databaseengine head node 420 may include a client-side storage service driver425. In this example, distributed database-optimized storage system 410includes multiple storage system server nodes (including those shown as430, 440, and 450), each of which includes storage for data pages andredo logs for the segment(s) it stores, and hardware and/or softwareconfigured to perform various segment management functions. For example,each storage system server node may include hardware and/or softwareconfigured to perform at least a portion of any or all of the followingoperations: replication (locally, e.g., within the storage node),coalescing of redo logs to generate data pages, crash recovery, and/orspace management (e.g., for a segment). Each storage system server nodemay also have multiple attached storage devices (e.g., SSDs) on whichdata blocks may be stored on behalf of clients (e.g., users, clientapplications, and/or database service subscribers).

In the example illustrated in FIG. 4, storage system server node 430includes data page(s) 433, segment redo log(s) 435, segment managementfunctions 437, and attached SSDs 471-478. Again note that the label“SSD” may or may not refer to a solid-state drive, but may moregenerally refer to a local block storage volume, regardless of itsunderlying hardware. Similarly, storage system server node 440 includesdata page(s) 443, segment redo log(s) 445, segment management functions447, and attached SSDs 481-488; and storage system server node 450includes data page(s) 453, segment redo log(s) 455, segment managementfunctions 457, and attached SSDs 491-498.

As previously noted, in some embodiments, a sector is the unit ofalignment on an SSD and may be the maximum size on an SSD that can bewritten without the risk that the write will only be partiallycompleted. For example, the sector size for various solid-state drivesand spinning media may be 4 KB. In some embodiments of the distributeddatabase-optimized storage systems described herein, each and everysector may include have a 64-bit (8 byte) CRC at the beginning of thesector, regardless of the higher-level entity of which the sector is apart. In such embodiments, this CRC (which may be validated every time asector is read from SSD) may be used in detecting corruptions. In someembodiments, each and every sector may also include a “sector type” bytewhose value identifies the sector as a log sector, a data sector, or anuninitialized sector. For example, in some embodiments, a sector typebyte value of 0 may indicate that the sector is uninitialized.

One embodiment of a method for accessing data in a database system thatincludes a database engine and a separate distributed database storageservice, such as those described herein, is illustrated by the flowdiagram in FIG. 5. As illustrated at 510, in this example, the methodmay include a database engine head node receiving (e.g., from a databaseclient) a write request directed to a data record in a database table.For example, the write request may specify that a new data record shouldbe added to the database table (or to a particular data page thereof) ormay specify a modification to an existing data record in a particulardata page of the database table. The method may include the databaseengine head node generating a redo log record specifying the requestedwrite, as in 520, and sending the redo log record (but not theparticular data page to which the request is directed) to a node of adistributed database-optimized storage system that stores the particulardata page, as in 530.

As illustrated in this example, the method may include, in response toreceiving the redo log record, the storage system node writing the redolog record to disk (or to another type of persistent storage media), andreturning a write acknowledgment to the database engine head node, as in540. In some embodiments, in response to receiving the writeacknowledgement, the database engine head node may return acorresponding write acknowledgement to the client from whom the writerequest was received (not shown). As illustrated in this example, atsome point in time (e.g., at a point in time subsequent to receiving theredo log record and returning the write acknowledgement), the method mayinclude the storage system node coalescing multiple redo log records forthe particular data page (including, for example, the redo log recordthat was written to disk at step 540) to generate an instantiation ofthe particular data page in its current state, as in 550. For example,coalescing the redo log may include applying to a previouslyinstantiated version of the particular data page all of the redo logsthat have been received by the storage system for the particular datapage but that have not yet been applied to an instance of the particulardata page to provide an up-to-date version of the particular data page.Note that in some embodiments, an up-to-date version of the particulardata page may be generated directly from one or more redo logs, e.g.,without applying them to a previously stored version of the particulardata page.

As illustrated in FIG. 5, the method may also include (e.g., at somepoint subsequent to coalescing redo logs to create an up-to-date versionof the particular data page) the database engine head node receiving aread request directed to the particular data page, as in 560. Inresponse, the database engine head node may send a corresponding readrequest to the storage node that stores the particular data page, as in570. Note that, in this example, it is assumed that the database enginehead node does not store a current version of the particular data pagein its cache. Otherwise, the method may include database engine headnode responding to the read request itself (e.g., by returning therequested data from its cache), rather than sending a corresponding readrequest to the storage system node. As illustrated in this example, themethod may include the storage system node returning the particular datapage to the database engine head node in its current state, as in 580,after which the database engine head node may return the requested datato the client from whom the read request was received, as in 590.

In various embodiments, the version of the particular data page that isreturned to the database engine head node (e.g., in step 580) may be thesame version that was generated by the coalescing operation in step 550,or may be a more recent version that was created by a subsequentcoalescing operation (e.g., one that applied additional redo log recordsthat were subsequent to the coalescing operation in step 550). Forexample, an additional coalescing operation may have been performed atthe storage system node in response to the receipt of the read requestfrom the database engine head node, as part of a database crash recoveryoperation, or in response to another type of trigger, in differentembodiments. Note that in some embodiments, the operations illustratedin FIG. 5 for accessing data in a database system that includes adatabase engine and a separate distributed database storage service maybe performed automatically (e.g., without user intervention) in thedatabase system in response to receiving a request to access the data.

In some embodiments, each of the storage system server nodes in thedistributed database-optimized storage system may implement a set ofprocesses running on the node server's operating system that managecommunication with the database engine head node, e.g., to receive redologs, send back data pages, etc. In some embodiments, all data blockswritten to the distributed database-optimized storage system may bebacked up to long-term and/or archival storage (e.g., in a remotekey-value durable backup storage system).

FIG. 6 is a block diagram illustrating the use of a separate distributeddatabase-optimized storage system in a database system, according to oneembodiment. In this example, one or more client processes 610 may storedata to one or more database tables maintained by a database system thatincludes a database engine 620 and a distributed database-optimizedstorage system 630. In the example illustrated in FIG. 6, databaseengine 620 includes database tier components 660 and client-side driver640 (which serves as the interface between distributeddatabase-optimized storage system 630 and database tier components 660).In some embodiments, database tier components 660 may perform functionssuch as those performed by query parsing, optimization and executioncomponent 305 and transaction and consistency management component 330of FIG. 3, and/or may store data pages, transaction logs and/or undologs (such as those stored by data page cache 335, transaction log 340and undo log 345 of FIG. 3).

In this example, one or more client processes 610 may send databasequery requests 615 (which may include read and/or write requeststargeting data stored on one or more of the storage nodes 635 a-635 n)to database tier components 660, and may receive database queryresponses 617 from database tier components 660 (e.g., responses thatinclude write acknowledgements and/or requested data). Each databasequery request 615 that includes a request to write to a data page may beparsed and optimized to generate one or more write record requests 641,which may be sent to client-side driver 640 for subsequent routing todistributed database-optimized storage system 630. In this example,client-side driver 640 may generate one or more redo log records 631corresponding to each write record request 641, and may send them tospecific ones of the storage nodes 635 of distributed database-optimizedstorage system 630. Distributed database-optimized storage system 630may return a corresponding write acknowledgement 623 for each redo logrecord 631 to database engine 620 (specifically to client-side driver640). Client-side driver 640 may pass these write acknowledgements todatabase tier components 660 (as write responses 642), which may thensend corresponding responses (e.g., write acknowledgements) to one ormore client processes 610 as one of database query responses 617.

In this example, each database query request 615 that includes a requestto read a data page may be parsed and optimized to generate one or moreread record requests 643, which may be sent to clients-side driver 640for subsequent routing to distributed database-optimized storage system630. In this example, client-side driver 640 may send these requests tospecific ones of the storage nodes 635 of distributed database-optimizedstorage system 630, and distributed database-optimized storage system630 may return the requested data pages 633 to database engine 620(specifically to client-side driver 640). Client-side driver 640 maysend the returned data pages to the database tier components 660 asreturn data records 644, and database tier components 660 may then sendthe data pages to one or more client processes 610 as database queryresponses 617.

In some embodiments, various error and/or data loss messages 634 may besent from distributed database-optimized storage system 630 to databaseengine 620 (specifically to client-side driver 640). These messages maybe passed from client-side driver 640 to database tier components 660 aserror and/or loss reporting messages 645, and then to one or more clientprocesses 610 along with (or instead of) a database query response 617.

In some embodiments, the APIs 631-634 of distributed database-optimizedstorage system 630 and the APIs 641-645 of client-side driver 640 mayexpose the functionality of the distributed database-optimized storagesystem 630 to database engine 620 as if database engine 620 were aclient of distributed database-optimized storage system 630. Forexample, database engine 620 (through client-side driver 640) may writeredo log records or request data pages through these APIs to perform (orfacilitate the performance of) various operations of the database systemimplemented by the combination of database engine 620 and distributeddatabase-optimized storage system 630 (e.g., storage, access, changelogging, recovery, and/or space management operations). As illustratedin FIG. 6, distributed database-optimized storage system 630 may storedata blocks on storage nodes 635 a-635 n, each of which may havemultiple attached SSDs. In some embodiments, distributeddatabase-optimized storage system 630 may provide high durability forstored data block through the application of various types of redundancyschemes.

Note that in various embodiments, the API calls and responses betweendatabase engine 620 and distributed database-optimized storage system630 (e.g., APIs 631-634) and/or the API calls and responses betweenclient-side driver 640 and database tier components 660 (e.g., APIs641-645) in FIG. 6 may be performed over a secure proxy connection(e.g., one managed by a gateway control plane), or may be performed overthe public network or, alternatively, over a private channel such as avirtual private network (VPN) connection. These and other APIs to and/orbetween components of the database systems described herein may beimplemented according to different technologies, including, but notlimited to, Simple Object Access Protocol (SOAP) technology andRepresentational state transfer (REST) technology. For example, theseAPIs may be, but are not necessarily, implemented as SOAP APIs orRESTful APIs. SOAP is a protocol for exchanging information in thecontext of Web-based services. REST is an architectural style fordistributed hypermedia systems. A RESTful API (which may also bereferred to as a RESTful web service) is a web service API implementedusing HTTP and REST technology. The APIs described herein may in someembodiments be wrapped with client libraries in various languages,including, but not limited to, C, C++, Java, C# and Perl to supportintegration with database engine 620 and/or distributeddatabase-optimized storage system 630.

As noted above, in some embodiments, the functional components of adatabase system may be partitioned between those that are performed bythe database engine and those that are performed in a separate,distributed, database-optimized storage system. In one specific example,in response to receiving a request from a client process (or a threadthereof) to insert something into a database table (e.g., to update asingle data block by adding a record to that data block), one or morecomponents of the database engine head node may perform query parsing,optimization, and execution, and may send each portion of the query to atransaction and consistency management component. The transaction andconsistency management component may ensure that no other client process(or thread thereof) is trying to modify the same row at the same time.For example, the transaction and consistency management component may beresponsible for ensuring that this change is performed atomically,consistently, durably, and in an isolated manner in the database. Forexample, the transaction and consistency management component may worktogether with the client-side storage service driver of the databaseengine head node to generate a redo log record to be sent to one of thenodes in the distributed database-optimized storage service and to sendit to the distributed database-optimized storage service (along withother redo logs generated in response to other client requests) in anorder and/or with timing that ensures the ACID properties are met forthis transaction. Upon receiving the redo log record (which may beconsidered an “update record” by the storage service), the correspondingstorage node may update the data block, and may update a redo log forthe data block (e.g., a record of all changes directed to the datablock). In some embodiments, the database engine may be responsible forgenerating an undo log record for this change, and may also beresponsible for generating a redo log record for the undo log, both ofwhich may be used locally (in the database tier) for ensuringtransactionality. However, unlike in traditional database systems, thesystems described herein may shift the responsibility for applyingchanges to data blocks to the storage system (rather than applying themat the database tier and shipping the modified data blocks to thestorage system).

One embodiment of a method for performing a write operation in adatabase system, from the perspective of the database engine, isillustrated by the flow diagram in FIG. 7. As illustrated at 710, inthis example, the method may include the database engine head nodereceiving (e.g., from a database client) a write request directed to adata record in a database table. For example, the write request mayspecify that a new data record should be added to the database table (orto a particular data page thereof) or may specify a modification to anexisting data record in a particular data page of the database table.The method may also include the database engine head node (or aparticular component thereof) parsing and/or optimizing the writerequest, as in 720. For example, in some embodiments, the databaseengine head node may be responsible for generating a query executionplan. As illustrated in FIG. 7, the method may include the databaseengine head node generating a redo log record specifying the requestedwrite, as in 730, and the database engine head node (or, morespecifically, a client-side storage service driver on the databaseengine head node) determining the node of a distributeddatabase-optimized storage system that stores the particular data pageto which the write request is directed, as in 740.

As illustrated in this example, the method may include the databaseengine head node (or, more specifically, the client-side storage servicedriver on the database engine head node) sending the redo log record,but not any version of the particular data page, to the determined nodeof storage system, as in 750. As illustrated in FIG. 7, there may be noother action taken by the database engine head node with respect to thewrite request until (and unless) the database engine head node (or, morespecifically, the client-side storage service driver on the databaseengine head node) receives an acknowledgment of the write from thestorage system. Once this acknowledgement is received (shown as thepositive exit from 760), the method may include the database engine headnode returning a corresponding write acknowledgment to the requestor(e.g., to the client from whom the write request was received), as in770. Note that in some embodiments, if a write acknowledgement is notreceived from the storage system within a pre-determined time period,the database engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) may beconfigured to determine that the determined storage node has failed (oris degraded) or that some other error condition exists in the storagesystem. Note also that the operations illustrated in FIG. 7 forperforming a write operation may be performed automatically (e.g.,without user intervention) in the database system in response toreceiving a write request.

One embodiment of a method for performing a write operation in adatabase system, from the perspective of a distributeddatabase-optimized storage system, is illustrated by the flow diagram inFIG. 8. As illustrated at 810, in this example, the method may include anode of a distributed database-optimized storage system receiving a redolog record that is directed to a particular data page that the nodestores (but not any version of the particular data page itself) from adatabase engine (e.g., from a client-side storage service driver of adatabase head node), or from another client of the storage system. Inresponse to receiving the redo log record, the method may include thestorage system node writing the redo log record for the page to one ormore disks (or to another type of persistent storage media), as in 820.For example, the storage system node may append the redo log record to aredo log for the particular data page that is stored on a particulardisk, or to any of a number of replicas of such a redo log that arestored on one or more disks in the same availability zone or in each oftwo or more different availability zones, in different embodiments. Onceone or more copies of the redo log record have been successfully written(according to a system-wide, application-specific, or client-specifieddurability policy), the method may also include the storage system nodereturning a write acknowledgment to the database engine (or other clientof the storage system) as in 830. Note that the storage system node mayreturn the write acknowledgement to the database engine at any timeafter successfully writing the redo log record, regardless of whether ornot the redo log record has been applied to a previously instantiatedversion of the particular data page to which it is directed on thestorage system node yet.

As illustrated in this example, if it is time for the storage systemnode to coalesce one or more redo log records for the particular datapage to create an up-to-date version of the particular data page (shownas the positive exit from 840), the method may include the storagesystem node applying one or more redo log records to the most recentlystored version of the particular data page to generate a new version ofthe particular data page in its current state, and writing that newversion of the particular data page to one or more disks (as in 850).For example, the coalesce operation may include the application of allredo log records that were received since the last coalesce operation(and/or that have not yet been applied to any version of the particulardata page) to the most recently instantiated version of the particulardata page. In other embodiments, a current version of the particulardata page may be generated directly from one or more redo logs, e.g.,without applying them to a previously stored version of the particulardata page. As described herein, there may be a variety of ways todetermine when it is time to coalesce pending redo log records for agiven data page, in different embodiments. For example, a coalesceoperation may be triggered for a data page at regular (e.g., periodic)time intervals, in response to receiving a single redo log targeting thedata page, in response to having received a pre-determined number ofredo log records targeting the data page or a pre-determined number ofredo log records targeting the data page within a given time period, inresponse to receiving a read request targeting the data page, inresponse to the initiation of a crash recovery operation, or accordingto any other suitable policy.

As illustrated in FIG. 8, if it is not time for the storage system nodeto coalesce redo log records for the particular data page (shown as thenegative exit from 840), but another redo log record targeting theparticular data page is received (shown as the positive exit from 860),the method may include repeating the operations illustrated at 820-860for the additional redo log record. In this example, as more redo logrecords targeting the particular data page are received by the storagesystem, the storage system node may repeat the operations illustrated at820-860 for each additional redo log record, and the storage system nodemay coalesce the redo log records for the particular data page from timeto time, according to one or more applicable triggers and/or policies.This is illustrated in FIG. 8 by the feedback from the positive exit of860 to 820, and the feedback from the negative exit of 860 to 840. Notethat the operations illustrated in FIG. 8 for performing a writeoperation may be performed automatically (e.g., without userintervention) in the storage system in response to receiving a redo logrecord.

Note that, in some embodiments, some data pages (e.g., data pages thatare rarely, if ever, accessed) may never be generated (e.g., through acoalesce operation) and/or persisted in memory. For example, in someembodiments, any redo log records directed to such data pages may bestored (e.g., persisted in memory) by one or more storage system nodes,but these redo log records may not be used to generate a completeversion of those data pages until or unless a request to read them isreceived. In such embodiments, even if a version of such a data page isgenerated (e.g., in response to a read request), it may not be persistedin memory (e.g., if it is unlikely to be accessed again soon, often, orever), but instead may be discarded at any point after it is returned tothe requestor.

A variety of different allocation models may be implemented for an SSD,in different embodiments. For example, in some embodiments, log entrypages and physical application pages may be allocated from a single heapof pages associated with an SSD device. This approach may have theadvantage of leaving the relative amount of storage consumed by logpages and data pages to remain unspecified and to adapt automatically tousage. It may also have the advantage of allowing pages to remainunprepared until they are used, and repurposed at will withoutpreparation. In other embodiments, an allocation model may partition thestorage device into separate spaces for log entries and data pages. Oncesuch allocation model is illustrated by the block diagram in FIG. 9 anddescribed below.

FIG. 9 is a block diagram illustrating how data and metadata may bestored on a given storage node (or persistent storage device) of adistributed database-optimized storage system, according to oneembodiment. In this example, SSD storage space 900 stores an SSD headerand other fixed metadata in the portion of the space labeled 910. Itstores log pages in the portion of the space labeled 920, and includes aspace labeled 930 that is initialized and reserved for additional logpages. One portion of SSD storage space 900 (shown as 940) isinitialized, but unassigned, and another portion of the space (shown as950) is uninitialized and unassigned. Finally, the portion of SSDstorage space 900 labeled 960 stores data pages.

In this example, the first usable log page slot is noted as 915, and thelast used log page slot (ephemeral) is noted as 925. The last reservedlog page slot is noted as 935, and the last usable log page slot isnoted as 945. In this example, the first used data page slot (ephemeral)is noted as 965. In some embodiments, the positions of each of theseelements (915, 925, 935, 945, and 965) within SSD storage space 900 maybe identified by a respective pointer.

In allocation approach illustrated in FIG. 9, valid log pages may bepacked into the beginning of the flat storage space. Holes that open updue to log pages being freed may be reused before additional log pageslots farther into the address space are used. For example, in the worstcase, the first n log page slots contain valid log data, where n is thelargest number of valid log pages that have ever simultaneously existed.In this example, valid data pages may be packed into the end of the flatstorage space. Holes that open up due to data pages being freed may bereused before additional data page slots lower in the address space areused. For example, in the worst case, the last m data pages containvalid data, where m is the largest number of valid data pages that haveever simultaneously existed.

In some embodiments, before a log page slot can become part of thepotential set of valid log page entries, it may need to be initializedto a value that cannot be confused for a valid future log entry page.This is implicitly true for recycled log page slots, since a retired logpage has enough metadata to never be confused for a new valid log page.However, when a storage device is first initialized, or when space isreclaimed that had potentially been used to store application datapages, the log page slots may need to be initialized before they areadded to the log page slot pool. In some embodiments,rebalancing/reclaiming log space may be performed as a background task.

In the example illustrated in FIG. 9, the current log page slot poolincludes the area between the first usable log page slot (at 915) andthe last reserved log page slot (925). In some embodiments, this poolmay safely grow up to last usable log page slot (925) withoutre-initialization of new log page slots (e.g., by persisting an updateto the pointer that identifies the last reserved log page slot, 935). Inthis example, beyond the last usable log page slot (which is identifiedby pointer 945), the pool may grow up to the first used data page slot(which is identified by pointer 965) by persisting initialized log pageslots and persistently updating the pointer for the last usable log pageslot (945). In this example, the previously uninitialized and unassignedportion of the SSD storage space 900 shown as 950 may be pressed intoservice to store log pages. In some embodiments, the current log pageslot pool may be shrunk down to the position of the last used log pageslot (which is identified by pointer) by persisting an update to thepointer for the last reserved log page slot (935).

In the example illustrated in FIG. 9, the current data page slot poolincludes the area between the last usable log page slot (which isidentified by pointer 945) and the end of SSD storage space 900. In someembodiments, the data page pool may be safely grown to the positionidentified by the pointer to the last reserved log page slot (935) bypersisting an update to the pointer to the last usable log page slot(945). In this example, the previously initialized, but unassignedportion of the SSD storage space 900 shown as 940 may be pressed intoservice to store data pages. Beyond this, the pool may be safely grownto the position identified by the pointer to the last used log page slot(925) by persisting updates to the pointers for the last reserved logpage slot (935) and the last usable log page slot (945), effectivelyreassigning the portions of SSD storage space 900 shown as 930 and 940to store data pages, rather than log pages. In some embodiments, thedata page slot pool may be safely shrunk down to the position identifiedby the pointer to the first used data page slot (965) by initializingadditional log page slots and persisting an update to the pointer to thelast usable log page slot (945).

In embodiments that employ the allocation approach illustrated in FIG.9, page sizes for the log page pool and the data page pool may beselected independently, while still facilitating good packing behavior.In such embodiments, there may be no possibility of a valid log pagelinking to a spoofed log page formed by application data, and it may bepossible to distinguish between a corrupted log and a valid log tailthat links to an as-yet-unwritten next page. In embodiments that employthe allocation approach illustrated in FIG. 9, at startup, all of thelog page slots up to the position identified by the pointer to the lastreserved log page slot (935) may be rapidly and sequentially read, andthe entire log index may be reconstructed (including inferredlinking/ordering). In such embodiments, there may be no need forexplicit linking between log pages, since everything can be inferredfrom LSN sequencing constraints.

In some embodiments, a segment may consist of three main parts (orzones): one that contains a hot log, one that contains a cold log, andone that contains user page data. Zones are not necessarily contiguousregions of an SSD. Rather, they can be interspersed at the granularityof the storage page. In addition, there may be a root page for eachsegment that stores metadata about the segment and its properties. Forexample, the root page for a segment may store the user page size forthe segment, the number of user pages in the segment, the currentbeginning/head of the hot log zone (which may be recorded in the form ofa flush number), the volume epoch, and/or access control metadata.

In some embodiments, the hot log zone may accept new writes from theclient as they are received by the storage node. Both Delta User LogRecords (DULRs), which specify a change to a user page in the form of adelta from the previous version of the page, and Absolute User LogRecords (AULRs), which specify the contents of a complete user page, maybe written completely into the log. Log records may be added to thiszone in approximately the order they are received (i.e. they are notsorted by LSN) and they can span across log pages. The log records maybe self-describing, e.g., they may contain an indication of their ownsize. In some embodiments, no garbage collection is performed in thiszone. Instead, space may be reclaimed by truncating from the beginningof the log after all required log records have been copied into the coldlog. Log sectors in the hot zone may be annotated with the most recentknown unconditional VDL each time a sector is written. Conditional VDLCLRs may be written into the hot zone as they are received, but only themost recently written VDL CLR may be meaningful.

In some embodiments, every time a new log page is written, it may beassigned a flush number. The flush number may be written as part ofevery sector within each log page. Flush numbers may be used todetermine which log page was written later when comparing two log pages.Flush numbers are monotonically increasing and scoped to an SSD (orstorage node). For example, a set of monotonically increasing flushnumbers is shared between all segments on an SSD (or all segments on astorage node).

In some embodiments, in the cold log zone, log records may be stored inincreasing order of their LSNs. In this zone, AULRs may not necessarilystore data in-line, depending on their size. For example, if they havelarge payloads, all or a portion of the payloads may be stored in thedata zone and they may point to where their data is stored in the datazone. In some embodiments, log pages in the cold log zone may be writtenone full page at a time, rather than sector-by-sector. Because log pagesin the cold zone are written a full page at a time, any log page in thecold zone for which the flush numbers in all sectors are not identicalmay be considered to be an incompletely written page and may be ignored.In some embodiments, in the cold log zone, DULRs may be able to spanacross log pages (up to a maximum of two log pages). However, AULRs maynot be able to span log sectors, e.g., so that a coalesce operation willbe able to replace a DULR with an AULR in a single atomic write.

In some embodiments, the cold log zone is populated by copying logrecords from the hot log zone. In such embodiments, only log recordswhose LSN is less than or equal to the current unconditional volumedurable LSN (VDL) may be eligible to be copied to the cold log zone.When moving log records from the hot log zone to the cold log zone, somelog records (such as many CLRs) may not need to be copied because theyare no longer necessary. In addition, some additional coalescing of userpages may be performed at this point, which may reduce the amount ofcopying required. In some embodiments, once a given hot zone log pagehas been completely written and is no longer the newest hot zone logpage, and all ULRs on the hot zone log page have been successfullycopied to the cold log zone, the hot zone log page may be freed andreused.

In some embodiments, garbage collection may be done in the cold log zoneto reclaim space occupied by obsolete log records, e.g., log recordsthat no longer need to be stored in the SSDs of the storage tier. Forexample, a log record may become obsolete when there is a subsequentAULR for the same user page and the version of the user page representedby the log record is not needed for retention on SSD. In someembodiments, a garbage collection process may reclaim space by mergingtwo or more adjacent log pages and replacing them with fewer new logpages containing all of the non-obsolete log records from the log pagesthat they are replacing. The new log pages may be assigned new flushnumbers that are larger than the flush numbers of the log pages they arereplacing. After the write of these new log pages is complete, thereplaced log pages may be added to the free page pool. Note that in someembodiments, there may not be any explicit chaining of log pages usingany pointers. Instead, the sequence of log pages may be implicitlydetermined by the flush numbers on those pages. Whenever multiple copiesof a log record are found, the log record present in the log page withhighest flush number may be considered to be valid and the others may beconsidered to be obsolete.

In some embodiments, e.g., because the granularity of space managedwithin a data zone (sector) may be different from the granularityoutside the data zone (storage page), there may be some fragmentation.In some embodiments, to keep this fragmentation under control, thesystem may keep track of the number of sectors used by each data page,may preferentially allocate from almost-full data pages, and maypreferentially garbage collect almost-empty data pages (which mayrequire moving data to a new location if it is still relevant). Notethat pages allocated to a segment may in some embodiments be repurposedamong the three zones. For example, when a page that was allocated to asegment is freed, it may remain associated with that segment for someperiod of time and may subsequently be used in any of the three zones ofthat segment. The sector header of every sector may indicate the zone towhich the sector belongs. Once all sectors in a page are free, the pagemay be returned to a common free storage page pool that is shared acrosszones. This free storage page sharing may in some embodiments reduce (oravoid) fragmentation.

In some embodiments, the distributed database-optimized storage systemsdescribed herein may maintain various data structures in memory. Forexample, for each user page present in a segment, a user page table maystore a bit indicating whether or not this user page is “cleared” (i.e.,whether it includes all zeroes), the LSN of the latest log record fromthe cold log zone for the page, and an array/list of locations of alllog records from the hot log zone for page. For each log record, theuser page table may store the sector number, the offset of the logrecord within that sector, the number of sectors to read within that logpage, the sector number of a second log page (if the log record spanslog pages), and the number of sectors to read within that log page. Insome embodiments, the user page table may also store the LSNs of everylog record from the cold log zone and/or an array of sector numbers forthe payload of the latest AULR if it is in the cold log zone.

In some embodiments of the distributed database-optimized storagesystems described herein, an LSN index may be stored in memory. An LSNindex may map LSNs to log pages within the cold log zone. Given that logrecords in cold log zone are sorted, it may be to include one entry perlog page. However, in some embodiments, every non-obsolete LSN may bestored in the index and mapped to the corresponding sector numbers,offsets, and numbers of sectors for each log record.

In some embodiments of the distributed database-optimized storagesystems described herein, a log page table may be stored in memory, andthe log page table may be used during garbage collection of the cold logzone. For example, the log page table may identify which log records areobsolete (e.g., which log records can be garbage collected) and how muchfree space is available on each log page.

In the storage systems described herein, an extent may be a logicalconcept representing a highly durable unit of storage that can becombined with other extents (either concatenated or striped) torepresent a volume. Each extent may be made durable by membership in asingle protection group. An extent may provide an LSN-type read/writeinterface for a contiguous byte sub-range having a fixed size that isdefined at creation. Read/write operations to an extent may be mappedinto one or more appropriate segment read/write operations by thecontaining protection group. As used herein, the term “volume extent”may refer to an extent that is used to represent a specific sub-range ofbytes within a volume.

As noted above, a volume may consist of multiple extents, eachrepresented by a protection group consisting of one or more segments. Insome embodiments, log records directed to different extents may haveinterleaved LSNs. For changes to the volume to be durable up to aparticular LSN it may be necessary for all log records up to that LSN tobe durable, regardless of the extent to which they belong. In someembodiments, the client may keep track of outstanding log records thathave not yet been made durable, and once all ULRs up to a specific LSNare made durable, it may send a Volume Durable LSN (VDL) message to oneof the protection groups in the volume. The VDL may be written to allsynchronous mirror segments for the protection group. This is sometimesreferred to as an “Unconditional VDL” and it may be periodicallypersisted to various segments (or more specifically, to variousprotection groups) along with write activity happening on the segments.In some embodiments, the Unconditional VDL may be stored in log sectorheaders.

In various embodiments, the operations that may be performed on asegment may include writing a DULR or AULR received from a client (whichmay involve writing the DULR or AULR to the tail of the hot log zone andthen updating the user page table), reading a cold user page (which mayinvolve locating the data sectors of the user page and returning themwithout needing to apply any additional DULRs), reading a hot user page(which may involve locating the data sectors of the most recent AULR forthe user page and apply any subsequent DULRs to the user page beforereturning it), and replacing DULRs with AULRs (which may involvecoalescing DULRs for a user page to create an AULR that replaces thelast DULR that was applied). As described herein coalescing is theprocess of applying DULRs to an earlier version of a user page to createa later version of the user page. Coalescing a user page may help reduceread latency because (until another DULR is written) all DULRs writtenprior to coalescing may not need to be read and applied on demand. Itmay also help reclaim storage space by making old AULRs and DULRsobsolete (provided there is no snapshot requiring the log records to bepresent). In some embodiments, a coalescing operation may includelocating a most recent AULR and applying any subsequent DULRs insequence without skipping any of the DULRs. As noted above, in someembodiments, coalescing may not be performed within the hot log zone.Instead, it may be performed within the cold log zone. In someembodiments, coalescing may also be performed as log records are copiedfrom the hot log zone to the cold log zone.

In some embodiments, the decision to coalesce a user page may betriggered by the size of the pending DULR chain for the page (e.g., ifthe length of the DULR chain exceeds a pre-defined threshold for acoalescing operation, according to a system-wide, application-specificor client-specified policy)), or by the user page being read by aclient.

FIG. 10 is a block diagram illustrating an example configuration of adatabase volume 1010, according to one embodiment. In this example, datacorresponding to each of various address ranges 1015 (shown as addressranges 1015 a-1015 e) is stored as different segments 1045 (shown assegments 1045 a-1045 n). More specifically, data corresponding to eachof various address ranges 1015 may be organized into different extents(shown as extents 1025 a-1025 b, and extents 1035 a-1035 h), and variousones of these extents may be included in different protection groups1030 (shown as 1030 a-1030 f), with or without striping (such as thatshown as stripe set 1020 a and stripe set 1020 b). In this example,protection group 1 illustrates the use of erasure coding. In thisexample, protection groups 2 and 3 and protection groups 6 and 7represent mirrored data sets of each other, while protection group 4represents a single-instance (non-redundant) data set. In this example,protection group 8 represents a multi-tier protection group thatcombines other protection groups (e.g., this may represent amulti-region protection group). In this example, stripe set 1 (1020 a)and stripe set 2 (1020 b) illustrates how extents (e.g., extents 1025 aand 1025 b) may be striped into a volume, in some embodiments.

More specifically, in this example, protection group 1 (1030 a) includesextents a-c (1035 a-1035 c), which include data from ranges 1-3 (1015a-1015 c), respectively, and these extents are mapped to segments 1-4(1045 a-1045 d). Protection group 2 (1030 b) includes extent d (1035 d),which includes data striped from range 4 (1015 d), and this extent ismapped to segments 5-7 (1045 e-1045 g). Similarly, protection group 3(1030 c) includes extent e (1035 e), which includes data striped fromrange 4 (1015 d), and is mapped to segments 8-9 (1045 h-1045 i); andprotection group 4 (1030 d) includes extent f (1035 f), which includesdata striped from range 4 (1015 d), and is mapped to segment 10 (1045j). In this example, protection group 6 (1030 e) includes extent g (1035g), which includes data striped from range 5 (1015 e), and is mapped tosegments 11-12 (1045 k-1045 l); and protection group 7 (1030 f) includesextent h (1035 h), which also includes data striped from range 5 (1015e), and is mapped to segments 13-14 (1045 m-1045 n).

One embodiment of a method for performing a read operation in a databasesystem, from the perspective of the database engine, is illustrated bythe flow diagram in FIG. 11. As illustrated at 1110, in this example,the method may include the database engine head node receiving (e.g.,from a database client), a read request directed to a particular datapage. The method may also include the database engine head node (or aparticular component thereof) parsing and/or optimizing the readrequest, as in 1120. For example, in some embodiments, the databaseengine head node may be responsible for generating a query executionplan. As illustrated in FIG. 11, if the particular data page is residentin the cache of the database engine head node, shown as the positiveexit from 1130, the method may include the database engine head nodereturning the requested data from the version of the particular datapage found in its cache, as in 1135. For example, in some embodiments,the database engine head node may temporality hold copies of the mostrecently accessed data pages in its cache, and may update those copiesin response to receiving write requests directed to them (e.g., inaddition to generating and passing redo log records for those writerequests to a distributed database-optimized storage system). In somesuch embodiments, if a particular data page targeted by a read operationis resident in the cache, it may be assumed to be an up-to-date versionof the particular data page (e.g., it may be assumed that all redo logrecords targeting the data page have already been applied to the versionof the particular data page that is stored in the cache).

As illustrated in FIG. 11, if the particular data page is not residentin the cache of the database engine head node, shown as the negativeexit from 1130, the method may include the database engine head node(or, more specifically, a client-side storage service driver on thedatabase engine head node) determining a node in a distributeddatabase-optimized storage system that stores the particular data page,and sending a corresponding read request to the determined storagesystem node, as in 1140. As illustrated in FIG. 11, there may be noother action taken by the database engine head node with respect to theread request until (and unless) the database engine head node (or, morespecifically, the client-side storage service driver on the databaseengine head node) receives the particular data page (in its currentstate) from the storage system. Once the database engine head node (or,more specifically, the client-side storage service driver on thedatabase engine head node) receives the particular data page in itscurrent state from the determined storage system node (shown as thepositive exit from 1150), the method may include the database enginehead node returning the requested data to the requestor (e.g., theclient from whom the read request was received), as in 1160. Forexample, if the version of the particular data page received from thedetermined storage system node is a version of the particular data pageto which all redo log records targeting the particular data page to datehave been applied (or at least all of the redo log records that could beapplied while maintaining the transactionality and consistencyproperties of the database system), the database engine head node mayreturn the requested data from the version of the particular data pagereceived from the determined storage system node. Note that in someembodiments, if a current copy of the particular data page is notreceived from the storage system within a pre-determined time period,the database engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) may beconfigured to determine that the determined storage node has failed (oris degraded) or that some other error condition exists in the storagesystem. Note also that the operations illustrated in FIG. 11 forperforming a read operation may be performed automatically (e.g.,without user intervention) in the database system in response toreceiving a read request.

One embodiment of a method for performing a read operation in a databasesystem, from the perspective of a distributed database-optimized storagesystem, is illustrated by the flow diagram in FIG. 12. As illustrated at1210, in this example, the method may include a node in a distributeddatabase-optimized storage system receiving a read request directed to aparticular data page that is stored by the storage system node. Indifferent embodiments, the storage system may receive the read requestfrom a database engine (e.g., from a client-side storage service driverof a database head node), or from another storage service client. Asillustrated in this example, if the storage system node stores anup-to-date copy of the data page (shown as the positive exit from 1220),the method may include the storage system node returning the up-to-datecopy of the data page that it already stores, as in 1250. For example,if all of the redo log records targeting the particular block that havebeen received by the storage system node to date (or at least all of theredo log records that could be applied while maintaining thetransactionality and consistency properties of the database system) havebeen applied to the particular data page (e.g., if they have beencoalesced to create a current version of the particular data page), thestorage system node may not need to perform an additional coalesceoperation on the redo log records for the particular data page beforereturning a response.

On the other hand, if the storage system node does not store anup-to-date copy of the data page (shown as the negative exit from 1220),the method may include the storage system node retrieving the mostrecently stored copy of the particular data page from disk or fromanother persistent storage device, as in 1230, and then applying changesspecified in one or more redo log records for the particular data pageto the retrieved copy of the particular data page to generate anup-to-date copy of the particular data page, as in 1240. For example,the storage system node may apply to the retrieved copy of theparticular data page any and all redo log records targeting theparticular data page that have been received by the storage system nodeto date, but that have not yet been applied to the particular data page.Once the storage system node has created the up-to-date copy of theparticular data page, the storage system node may return the newlycreated copy of the particular data page to the database engine (orother storage system client) as the up-to-date copy of the data page (asin 1250). Note that the operations illustrated in FIG. 12 for performinga read operation may be performed automatically (e.g., without userintervention) in the storage system in response to receiving a readrequest.

As previously noted, a protection group (PG) is an abstract distributedentity that represents a unit of durability formed by a collection ofsegments. In some embodiments, a protection group may represent one ormore extents within a volume. A protection group may expose interfacesfor one or more extents, and may encapsulate (and hide) one or moresegments and associated metadata. The protection group may beresponsible for maintaining durability of the extents that it exposes,according to durability policy configured for the protection group. Insome embodiments, a protection group may achieve durability of all ofits constituent extents by using redundant segments to persist extentdata, and by actively maintaining such redundancy. The way in which theprotection group maps extent read/write operations onto the underlyingsegments may be opaque to the users of the extents. Different redundancystrategies may be employed in different embodiments, including, but notlimited to extent mirroring, extent erasure coding, and/or lazyreplication.

A “mirrored protection group” is a protection group in which each of theconstituent segments is a synchronous mirrored copy of a single extent.In this model, a change is considered durable if it has been madedurable on all affected synchronous mirrored segments within theprotection group. Protection groups may be formed within a singleavailability zone or across multiple availability zones. For example,for a protection group that encapsulates only segments within aparticular availability zone, the availability of the protection groupmay be tied directly to availability of the associated availabilityzone. In some embodiments, a regional protection group may encapsulatesegments across multiple availability zones. In some such embodiments,the regional protection group may be implemented as a collection ofcorresponding AZ Protection Groups, one from each AZ.

One embodiment of a method for performing read and write operations in adistributed database-optimized storage system that includes protectiongroups is illustrated by the flow diagram in FIG. 13. As illustrated at1310, in this example, the method may include a database engine headnode of a database tier receiving (e.g., from a database client) a writerequest directed to a data record in a database table. For example, thewrite request may specify that a new data record should be added to thedatabase table (or to a particular data page thereof) or may specify amodification to an existing data record in a particular data page of thedatabase table. In response to receiving the write request, the methodmay include the database engine head node (or, more specifically, aclient-side storage service driver on the database engine head node)sending a redo log record (but not a copy of the particular data page towhich the write request is directed) to two or more storage nodes in aprotection group of a distributed database-optimized storage system thatstore the particular data page to which the request is directed, as in1320.

As illustrated in this example, until the database engine head node (or,more specifically, the client-side storage service driver on thedatabase engine head node) receives an acknowledgement that the writewas successfully completed from a quorum of the storage nodes in theprotection group, the database engine head node may wait to receive awrite acknowledgement from a quorum of the storage nodes in theprotection group. This is illustrated in FIG. 13 by the feedback fromthe negative exit from 1330 to the input to 1330. Once the databaseengine head node has received a write acknowledgement from a quorum ofthe storage nodes in the protection group (shown as the positive exitfrom 1330), the method may include the database engine head nodereturning a corresponding write acknowledgement to the requestor (e.g.,to the database client), as in 1340. Note that in some embodiments, if awrite acknowledgement is not received from a quorum of the storage nodesin the protection group within a pre-determined time period, thedatabase engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) may beconfigured to determine that one or more of the storage nodes in theprotection group have failed (or are degraded) or that some other errorcondition exists in the storage system.

As illustrated in FIG. 13, the method may include (e.g., at some pointin time subsequent to receiving and responding to the write request),the database engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) receiving aread request directed to the particular data page (as in 1350). Inresponse to receiving the read request, the method may include thedatabase engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) sending a readrequest to two or more storage nodes in the protection group that storethe particular data page (as in 1360).

As illustrated in this example, until the database engine head node (or,more specifically, the client-side storage service driver on thedatabase engine head node) receives a current copy of the particulardata page from a quorum of the storage nodes in the protection group,the database engine head node may wait to receive a current copy of theparticular data page from a quorum of the storage nodes in theprotection group. For example, in some embodiments, one or more of thestorage nodes in the protection group may not store a current copy ofthe particular data page and may have to create a current copy of theparticular data page by applying one or more pending redo log records toan earlier version of the particular data page (e.g., in a coalesceoperation) before responding. This is illustrated in FIG. 13 by thefeedback from the negative exit from 1370 to the input to 1370. Once thedatabase engine head node has received a current copy of the particulardata page from a quorum of the storage nodes in the protection group(shown as the positive exit from 1370), the method may include thedatabase engine head node returning a current copy of the data page tothe requestor (e.g., to the database client), as in 1380. Note that insome embodiments, if a current copy of the particular data page is notreceived from a quorum of the storage nodes in the protection groupwithin a pre-determined time period, the database engine head node (or,more specifically, the client-side storage service driver on thedatabase engine head node) may be configured to determine that one ormore of the storage nodes in the protection group have failed (or aredegraded) or that some other error condition exists in the storagesystem. Note also that the operations illustrated in FIG. 13 forperforming write operations or for performing read operations may beperformed automatically (e.g., without user intervention) in thedatabase system in response to receiving requests to do so.

Some existing database systems flush all data pages to disk periodically(e.g., checkpointing all of the pages once every 5 minutes). In suchsystems, if there is a crash, the system might have to replay a largenumber of redo log records to re-create the current version of a datapage to which a lot of changes were directed since the last time thatdata page was flushed. For example, this may be the case for a hot datapage in the cache to which large numbers of changes are continuouslydirected, such as a page in which a sequence number is incremented eachtime an incoming order is received in an e-commerce application. Insteadof checkpointing all data pages stored in the system at one time, in thesystems described herein, checkpointing may be performed on a data block(e.g., data page) basis, rather than on a database or segment basis. Forexample, in some embodiments, checkpointing may be performed at eachstorage node, and each of the data pages stored on a particular storagenode may be coalesced to create a new version of data page (e.g., acheckpoint of that data page) on the storage node only when it iswarranted (e.g., when the number of redo log records its own redo logreaches a pre-determined number). In such embodiments, the database tiermay not be involved in checkpointing at all. Instead, checkpointing maybe a distributed process (e.g., a background process) that is theresponsibility of the storage nodes themselves. Note that becausecheckpointing may be performed by a background process on the storagetier (which may have visibility into other foreground and/or backgroundactivities affecting each storage node), in some embodiments, thestorage tier (or one of the storage system server nodes thereof) may beconfigured to postpone a checkpointing operation for a particularstorage node if it is being heavily loaded by another foreground orbackground process. In some embodiments, postponing a checkpointingoperation may prevent checkpointing from adversely affecting foregroundlatency.

In some embodiments, various in-memory data structures (such as thosedescribed herein) may be needed for a segment to function. In someembodiments, these in-memory structures may be built up during startup(e.g., following a crash) by doing a full scan of all log pages. In someembodiments, periodic checkpoints of some of these in-memory datastructures may be performed to reduce startup time following a crash.

In some existing database systems, the database tier may need to writedata pages out to the storage layer at the same frequency at whichchanges are being received, otherwise, if the cache gets full of dirtiedpages that have not yet been written out to the storage layer, a pagemay have to be flushed in order to accept more changes, which introduceslatency into the system. By contrast, in the systems described herein,as long as the redo logs for a data page in the cache of the databaseengine head node have been passed to the distributed storage system (anda write acknowledgement has been received), the database tier may evictthe data page (which can be reconstructed by the storage layer at anytime) from its cache.

In some embodiments of the systems described herein, crash recovery,flashback, and point in time restore operations may not require thereplay of either redo or undo logs. Instead, they may include buildingan instance, resetting the current volume LSN to the appropriate commitpoint, and restarting the database service.

The database systems described herein may in some embodiments be scaledto accommodate larger database tables and/or higher throughput than someexisting databases, without suffering some of the disadvantagesassociated with previous database scaling approaches (e.g.,disadvantages in terms of complexity and/or cost). For example, in someembodiments, there may be no practical limit to the volume size, andvolumes may be able to grow dynamically without loss of availability orchange in performance (e.g., by adding an additional protection group ofsegments). In addition, assuming write traffic is spread acrosssegments, IOPS may be made virtually unbounded. For example, in someembodiments, IOPS may be increased or decreased without impacting theperformance of the currently running database, with any necessaryrestriping being performed in the background while new writes areforwarded to the storage tier. In such embodiments, query performancemay be made predictable and consistent without the need to freeze IOtraffic during backup operations or re-mirroring. Instead, the storagetier may manage striping, mirroring and heat management, removing theseresponsibilities from the database tier or administrator.

As described herein, all writes in the storage tier may be made durableon persistent media before being acknowledged back to the database tier.This may prevent logical corruptions on large-scale power events, andmay remove the need to restore from backup, in such cases. In someembodiments, the only time a restore from backup is required may be inresponse to a customer error (e.g., the accidental deletion of a table,or similar).

In some embodiments, since replication operations involve moving logrecords, and not data blocks, the performance impact of replication maybe much lower than in other database systems. In addition, coordinationof writes across availability zones may be performed at the storage tierand may not require the use of a reserved database standby node forsynchronous replication, which may reduce costs when compared withexisting database systems.

The methods described herein may in various embodiments be implementedby any combination of hardware and software. For example, in oneembodiment, the methods may be implemented by a computer system thatincludes one or more processors executing program instructions stored ona computer-readable storage medium coupled to the processors. Theprogram instructions may be configured to implement the functionalitydescribed herein (e.g., the functionality of various servers and othercomponents that implement the database services/systems and/or storageservices/systems described herein).

FIG. 14 is a block diagram illustrating a computer system configured toimplement at least a portion of the database systems described herein,according to various embodiments. For example, computer system 1400 maybe configured to implement a database engine head node of a databasetier, or one of a plurality of storage nodes of a separate distributeddatabase-optimized storage system that stores database tables andassociated metadata on behalf of clients of the database tier, indifferent embodiments. Computer system 1400 may be any of various typesof devices, including, but not limited to, a personal computer system,desktop computer, laptop or notebook computer, mainframe computersystem, handheld computer, workstation, network computer, a consumerdevice, application server, storage device, telephone, mobile telephone,or in general any type of computing device.

Computer system 1400 includes one or more processors 1410 (any of whichmay include multiple cores, which may be single or multi-threaded)coupled to a system memory 1420 via an input/output (I/O) interface1430. Computer system 1400 further includes a network interface 1440coupled to I/O interface 1430. In various embodiments, computer system1400 may be a uniprocessor system including one processor 1410, or amultiprocessor system including several processors 1410 (e.g., two,four, eight, or another suitable number). Processors 1410 may be anysuitable processors capable of executing instructions. For example, invarious embodiments, processors 1410 may be general-purpose or embeddedprocessors implementing any of a variety of instruction setarchitectures (ISAs), such as the x86, PowerPC, SPARC, or MIPS ISAs, orany other suitable ISA. In multiprocessor systems, each of processors1410 may commonly, but not necessarily, implement the same ISA. Thecomputer system 1400 also includes one or more network communicationdevices (e.g., network interface 1440) for communicating with othersystems and/or components over a communications network (e.g. Internet,LAN, etc.). For example, a client application executing on system 1400may use network interface 1440 to communicate with a server applicationexecuting on a single server or on a cluster of servers that implementone or more of the components of the database systems described herein.In another example, an instance of a server application executing oncomputer system 1400 may use network interface 1440 to communicate withother instances of the server application (or another serverapplication) that may be implemented on other computer systems (e.g.,computer systems 1490).

In the illustrated embodiment, computer system 1400 also includes one ormore persistent storage devices 1460 and/or one or more I/O devices1480. In various embodiments, persistent storage devices 1460 maycorrespond to disk drives, tape drives, solid state memory, other massstorage devices, or any other persistent storage device. Computer system1400 (or a distributed application or operating system operatingthereon) may store instructions and/or data in persistent storagedevices 1460, as desired, and may retrieve the stored instruction and/ordata as needed. For example, in some embodiments, computer system 1400may host a storage system server node, and persistent storage 1460 mayinclude the SSDs attached to that server node.

Computer system 1400 includes one or more system memories 1420 that areconfigured to store instructions and data accessible by processor(s)1410. In various embodiments, system memories 1420 may be implementedusing any suitable memory technology, (e.g., one or more of cache,static random access memory (SRAM), DRAM, RDRAM, EDO RAM, DDR 10 RAM,synchronous dynamic RAM (SDRAM), Rambus RAM, EEPROM,non-volatile/Flash-type memory, or any other type of memory). Systemmemory 1420 may contain program instructions 1425 that are executable byprocessor(s) 1410 to implement the methods and techniques describedherein. In various embodiments, program instructions 1425 may be encodedin platform native binary, any interpreted language such as Java™byte-code, or in any other language such as C/C++, Java™, etc., or inany combination thereof. For example, in the illustrated embodiment,program instructions 1425 include program instructions executable toimplement the functionality of a database engine head node of a databasetier, or one of a plurality of storage nodes of a separate distributeddatabase-optimized storage system that stores database tables andassociated metadata on behalf of clients of the database tier, indifferent embodiments. In some embodiments, program instructions 1425may implement multiple separate clients, server nodes, and/or othercomponents.

In some embodiments, program instructions 1425 may include instructionsexecutable to implement an operating system (not shown), which may beany of various operating systems, such as UNIX, LINUX, Solaris™, MacOS™,Windows™, etc. Any or all of program instructions 1425 may be providedas a computer program product, or software, that may include anon-transitory computer-readable storage medium having stored thereoninstructions, which may be used to program a computer system (or otherelectronic devices) to perform a process according to variousembodiments. A non-transitory computer-readable storage medium mayinclude any mechanism for storing information in a form (e.g., software,processing application) readable by a machine (e.g., a computer).Generally speaking, a non-transitory computer-accessible medium mayinclude computer-readable storage media or memory media such as magneticor optical media, e.g., disk or DVD/CD-ROM coupled to computer system1400 via I/O interface 1430. A non-transitory computer-readable storagemedium may also include any volatile or non-volatile media such as RAM(e.g. SDRAM, DDR SDRAM, RDRAM, SRAM, etc.), ROM, etc., that may beincluded in some embodiments of computer system 1400 as system memory1420 or another type of memory. In other embodiments, programinstructions may be communicated using optical, acoustical or other formof propagated signal (e.g., carrier waves, infrared signals, digitalsignals, etc.) conveyed via a communication medium such as a networkand/or a wireless link, such as may be implemented via network interface1440.

In some embodiments, system memory 1420 may include data store 1445,which may be configured as described herein. For example, theinformation described herein as being stored by the database tier (e.g.,on a database engine head node), such as a transaction log, an undo log,cached page data, or other information used in performing the functionsof the database tiers described herein may be stored in data store 1445or in another portion of system memory 1420 on one or more nodes, inpersistent storage 1460, and/or on one or more remote storage devices1470, at different times and in various embodiments. Similarly, theinformation described herein as being stored by the storage tier (e.g.,redo log records, coalesced data pages, and/or other information used inperforming the functions of the distributed storage systems describedherein) may be stored in data store 1445 or in another portion of systemmemory 1420 on one or more nodes, in persistent storage 1460, and/or onone or more remote storage devices 1470, at different times and invarious embodiments. In general, system memory 1420 (e.g., data store1445 within system memory 1420), persistent storage 1460, and/or remotestorage 1470 may store data blocks, replicas of data blocks, metadataassociated with data blocks and/or their state, database configurationinformation, and/or any other information usable in implementing themethods and techniques described herein.

In one embodiment, I/O interface 1430 may be configured to coordinateI/O traffic between processor 1410, system memory 1420 and anyperipheral devices in the system, including through network interface1440 or other peripheral interfaces. In some embodiments, I/O interface1430 may perform any necessary protocol, timing or other datatransformations to convert data signals from one component (e.g., systemmemory 1420) into a format suitable for use by another component (e.g.,processor 1410). In some embodiments, I/O interface 1430 may includesupport for devices attached through various types of peripheral buses,such as a variant of the Peripheral Component Interconnect (PCI) busstandard or the Universal Serial Bus (USB) standard, for example. Insome embodiments, the function of I/O interface 1430 may be split intotwo or more separate components, such as a north bridge and a southbridge, for example. Also, in some embodiments, some or all of thefunctionality of I/O interface 1430, such as an interface to systemmemory 1420, may be incorporated directly into processor 1410.

Network interface 1440 may be configured to allow data to be exchangedbetween computer system 1400 and other devices attached to a network,such as other computer systems 1490 (which may implement one or morestorage system server nodes, database engine head nodes, and/or clientsof the database systems described herein), for example. In addition,network interface 1440 may be configured to allow communication betweencomputer system 1400 and various I/O devices 1450 and/or remote storage1470. Input/output devices 1450 may, in some embodiments, include one ormore display terminals, keyboards, keypads, touchpads, scanning devices,voice or optical recognition devices, or any other devices suitable forentering or retrieving data by one or more computer systems 1400.Multiple input/output devices 1450 may be present in computer system1400 or may be distributed on various nodes of a distributed system thatincludes computer system 1400. In some embodiments, similar input/outputdevices may be separate from computer system 1400 and may interact withone or more nodes of a distributed system that includes computer system1400 through a wired or wireless connection, such as over networkinterface 1440. Network interface 1440 may commonly support one or morewireless networking protocols (e.g., Wi-Fi/IEEE 802.11, or anotherwireless networking standard). However, in various embodiments, networkinterface 1440 may support communication via any suitable wired orwireless general data networks, such as other types of Ethernetnetworks, for example. Additionally, network interface 1440 may supportcommunication via telecommunications/telephony networks such as analogvoice networks or digital fiber communications networks, via storagearea networks such as Fibre Channel SANs, or via any other suitable typeof network and/or protocol. In various embodiments, computer system 1400may include more, fewer, or different components than those illustratedin FIG. 14 (e.g., displays, video cards, audio cards, peripheraldevices, other network interfaces such as an ATM interface, an Ethernetinterface, a Frame Relay interface, etc.)

It is noted that any of the distributed system embodiments describedherein, or any of their components, may be implemented as one or moreweb services. For example, a database engine head node within thedatabase tier of a database system may present database services and/orother types of data storage services that employ the distributed storagesystems described herein to clients as web services. In someembodiments, a web service may be implemented by a software and/orhardware system designed to support interoperable machine-to-machineinteraction over a network. A web service may have an interfacedescribed in a machine-processable format, such as the Web ServicesDescription Language (WSDL). Other systems may interact with the webservice in a manner prescribed by the description of the web service'sinterface. For example, the web service may define various operationsthat other systems may invoke, and may define a particular applicationprogramming interface (API) to which other systems may be expected toconform when requesting the various operations.

In various embodiments, a web service may be requested or invokedthrough the use of a message that includes parameters and/or dataassociated with the web services request. Such a message may beformatted according to a particular markup language such as ExtensibleMarkup Language (XML), and/or may be encapsulated using a protocol suchas Simple Object Access Protocol (SOAP). To perform a web servicesrequest, a web services client may assemble a message including therequest and convey the message to an addressable endpoint (e.g., aUniform Resource Locator (URL)) corresponding to the web service, usingan Internet-based application layer transfer protocol such as HypertextTransfer Protocol (HTTP).

In some embodiments, web services may be implemented usingRepresentational State Transfer (“RESTful”) techniques rather thanmessage-based techniques. For example, a web service implementedaccording to a RESTful technique may be invoked through parametersincluded within an HTTP method such as PUT, GET, or DELETE, rather thanencapsulated within a SOAP message.

The various methods as illustrated in the figures and described hereinrepresent example embodiments of methods. The methods may be implementedmanually, in software, in hardware, or in a combination thereof. Theorder of any method may be changed, and various elements may be added,reordered, combined, omitted, modified, etc.

Although the embodiments above have been described in considerabledetail, numerous variations and modifications may be made as wouldbecome apparent to those skilled in the art once the above disclosure isfully appreciated. It is intended that the following claims beinterpreted to embrace all such modifications and changes and,accordingly, the above description to be regarded in an illustrativerather than a restrictive sense.

The invention claimed is:
 1. A computing system, comprising: a pluralityof computing nodes, each of which comprises at least one processor and amemory; wherein one or more of the plurality of computing nodes isconfigured to implement a database service, and wherein the databaseservice comprises a database engine head node; wherein two or more otherones of the plurality of computing nodes are configured to implementserver nodes of a distributed storage service that stores portions ofdatabase tables as respective data pages on one or more storage devices;wherein the database engine head node is configured to: receive, from aclient of the database service, a write request directed to a given datarecord in a database table, wherein the write request specifies amodification to be made to the given data record; generate a redo logrecord representing the modification to be made to the given datarecord; send the redo log record, but not a data page comprising thegiven data record, to a particular server node of the distributedstorage service that stores a version of the data page comprising thegiven data record; wherein the particular server node of the distributedstorage service is configured to: receive the redo log record from thedatabase engine head node; write the redo log record to one or morestorage devices; return, to the database engine head node, anacknowledgement that the redo log record was written; and subsequent toreturning the acknowledgement: generate a current version of the datapage comprising the given data record, wherein to generate the currentversion of the data page, the particular server node of the distributedstorage service is configured to apply the received redo log record andone or more other redo log records representing modifications to thedata page to a previously stored version of the data page; and write thecurrent version of the data page to one or more storage devices.
 2. Thecomputing system of claim 1, wherein the database engine head node isfurther configured to: receive, from a database client, a request toread the data page comprising the given data record; and in response toreceiving the request to read the data page, send a request for acurrent version of the data page to the particular server node of thedistributed storage service.
 3. The computing system of claim 2, whereinthe particular server node of the distributed storage service is furtherconfigured to: receive, from the database engine head node, the requestfor the current version of the data page comprising the given datarecord; and in response to receiving the request for the current versionof the data page, return the current version of the data page to thedatabase engine head node.
 4. The computing system of claim 3, whereingenerating the current version of the data page is performed in responseto receiving the request for the current version of the data page. 5.The computing system of claim 1, wherein the database engine head nodecomprises a client-side driver for the distributed storage system; andwherein to send the redo log record to the particular server node of thedistributed storage system, the client-side driver is configured to:determine the particular server node of the distributed storage servicethat stores a version of the data page comprising the given data record;and send the redo log record to the particular server node of thedistributed storage system on behalf of the database service.
 6. Asystem, comprising: one or more computing nodes, each of which comprisesat least one processor and a memory, wherein the one or more computingnodes are configured to collectively implement a database service, andwhere the database service comprises a database engine head node and aninterface to a distributed storage system; wherein the database enginehead node is configured to: receive, from a client of the databaseservice, a write request directed to a given data record in a databasetable, wherein the write request specifies a modification to be made tothe given data record; generate a redo log record representing themodification to be made to the given data record; send, via theinterface, the redo log record, but not a data page comprising the givendata record, to a particular server node of the distributed storageservice that stores a version of the data page comprising the given datarecord; receive, via the interface, an acknowledgment that the redo logrecord has been written to the distributed storages service; and return,to the database client, a response indicating that the requested writehas been performed; receive, from a client of the database service, arequest to read the data page comprising the given data record; and inresponse to receiving the request to read the data page: send, via theinterface, a request for a current version of the data page to theparticular server node of the distributed storage service; receive, viathe interface, the current version of the data page; and return, to theclient from which the request to read the data page was received, thecurrent version of the data page.
 7. The system of claim 6, wherein thedatabase engine head node comprises a cache that stores recentlyaccessed data pages; wherein the database engine head node is configuredto send the request for the current version of the data page to theparticular server node in response to determining that a current versionof the data page is not present in the cache.
 8. The system of claim 6,wherein the database engine head node comprises a cache that storesrecently accessed data pages; wherein the cache stores a copy of thedata page comprising the given data record; and wherein the databaseengine head node is further configured to apply the modificationspecified in the write request to the given data record in the cachedcopy of the data page.
 9. The system of claim 6, wherein the databaseengine head node is further configured to: prior to sending the redo logrecord, determine the particular server node of the distributed storageservice that stores a version of the data page comprising the given datarecord, wherein determining the particular server node is performed bythe interface to the distributed storage system.
 10. The system of claim6, wherein the database engine head node is further configured to:receive, from one or more clients of the database service, two or moreadditional write requests directed to the database table; and servicethe two or more additional write requests, wherein servicing the two ormore additional write requests comprises enforcing atomicity, isolation,and consistency properties of transactions that target the databasetable.
 11. A non-transitory computer-readable storage medium storingprogram instructions that when executed on one or more computers causethe one or more computers to perform: receiving a query comprising awrite request targeting a data block that is stored in a distributedstorage system, wherein the write request specifies a modification to bemade to the data block; generating a redo log record representing themodification to be made to the data block; determining a node in thedistributed storage system that stores the data block; sending the redolog record, but not a copy of the data block, to the determined node inthe distributed storage system; and receiving an acknowledgement fromthe determined node in the distributed storage system that the redo logrecord has been written to a storage device on the determined node;determining one or more other nodes in the distributed storage systemthat store the data block, wherein the one or more other nodes are partof a same protection group as the determined node; and sending the redolog record, but not a copy of the data block, to the one or more othernodes in the distributed storage system.
 12. The non-transitorycomputer-readable storage medium of claim 11, wherein when executed onthe one or more computers, the program instructions further cause theone or more computers to perform, prior to said generating a redo log:parsing the query; and generating a query execution plan.
 13. Thenon-transitory computer-readable storage medium of claim 11, whereinwhen executed on the one or more computers, the program instructionsfurther cause the one or more computers to perform: receiving anacknowledgement from a quorum of nodes in the protection group that theredo log record has been written to a storage device on each of thenodes in the quorum of nodes; and in response to receiving anacknowledgement from the quorum of nodes, returning, to a client fromwhich the query was received, a query response indicating that the writerequest has been committed.
 14. The non-transitory computer-readablestorage medium of claim 11, wherein the query is received from adatabase service.